--- a/doc/interpreter/audio.txi	Thu Aug 21 18:49:47 2014 +0100
+++ b/doc/interpreter/audio.txi	Thu Aug 21 15:57:18 2014 -0700
@@ -32,8 +32,8 @@
 There are many different formats for representing such data.  Currently,
 only the two most popular, @emph{linear encoding} and @emph{mu-law
 encoding}, are supported by Octave.  There is an excellent FAQ on audio
-formats by Guido van Rossum @email{guido@@cwi.nl} which can be found at any
-FAQ ftp site, in particular in the directory
+formats by @nospell{Guido van Rossum} @email{guido@@cwi.nl} which can be
+found at any FAQ ftp site, in particular in the directory
 @file{/pub/usenet/news.answers/audio-fmts} of the archive site
 @code{rtfm.mit.edu}.
 

--- a/doc/interpreter/diagperm.txi	Thu Aug 21 18:49:47 2014 +0100
+++ b/doc/interpreter/diagperm.txi	Thu Aug 21 15:57:18 2014 -0700
@@ -462,7 +462,8 @@
 
 @noindent
 Finally, here's how to solve a linear system @code{A*x = b}
-with Tikhonov regularization (ridge regression) using SVD (a skeleton only):
+with @nospell{Tikhonov} regularization (ridge regression) using SVD (a skeleton
+only):
 
 @example
 @group

--- a/doc/interpreter/diffeq.txi	Thu Aug 21 18:49:47 2014 +0100
+++ b/doc/interpreter/diffeq.txi	Thu Aug 21 15:57:18 2014 -0700
@@ -54,7 +54,7 @@
 @end ifnottex
 
 @noindent
-using Hindmarsh's ODE solver @sc{lsode}.
+using @nospell{Hindmarsh's} ODE solver @sc{lsode}.
 
 
 
@@ -106,9 +106,10 @@
 @end group
 @end example
 
-See Alan C. Hindmarsh, @cite{ODEPACK, A Systematized Collection of ODE
-Solvers}, in Scientific Computing, R. S. Stepleman, editor, (1983) for
-more information about the inner workings of @code{lsode}.
+See @nospell{Alan C. Hindmarsh},
+@cite{ODEPACK, A Systematized Collection of ODE Solvers},
+in Scientific Computing, @nospell{R. S. Stepleman}, editor, (1983)
+for more information about the inner workings of @code{lsode}.
 
 An m-file for the differential equation used above is included with the
 Octave distribution in the examples directory under the name
@@ -139,8 +140,8 @@
 @ifnottex
 @math{x-dot}
 @end ifnottex
-is the derivative of @math{x}.  The equation is solved using Petzold's
-DAE solver @sc{daspk}.
+is the derivative of @math{x}.  The equation is solved using
+@nospell{Petzold's} DAE solver @sc{daspk}.
 
 @DOCSTRING(daspk)
 
@@ -158,6 +159,6 @@
 
 @DOCSTRING(dasrt_options)
 
-See K. E. Brenan, et al., @cite{Numerical Solution of Initial-Value
+See @nospell{K. E. Brenan}, et al., @cite{Numerical Solution of Initial-Value
 Problems in Differential-Algebraic Equations}, North-Holland (1989) for
 more information about the implementation of @sc{dassl}.

--- a/doc/interpreter/doccheck/aspell-octave.en.pws	Thu Aug 21 18:49:47 2014 +0100
+++ b/doc/interpreter/doccheck/aspell-octave.en.pws	Thu Aug 21 15:57:18 2014 -0700
@@ -1,5 +1,4 @@
 personal_ws-1.1 en 1
-Abramowitz
 accumarray
 Acknowledgements
 acknowledgements
@@ -7,11 +6,9 @@
 adams
 Affero
 afterwards
-Ahalt
 aifm
 AIX
 al
-Alamos
 aleph
 alnum
 alphanum
@@ -28,7 +25,6 @@
 ARMA
 arpack
 ascii
-Ashok
 ast
 async
 atan
@@ -56,7 +52,6 @@
 bartlett
 BaseValue
 basevalue
-Bateman
 BDF
 bdf
 betacdf
@@ -66,7 +61,6 @@
 betarnd
 BFGS
 bigtriangledown
-Bilbert
 bincoeff
 binocdf
 binoinv
@@ -91,9 +85,7 @@
 brackety
 braindead
 breakpoint
-Brenan
 broadcastable
-Brockwell
 BSX
 builtin
 builtins
@@ -121,7 +113,6 @@
 changelogs
 changeset
 changesets
-Chaves
 chdir
 Chebyshev
 chisq
@@ -137,7 +128,6 @@
 circum
 classpath
 classpaths
-Clenshaw
 CLI
 clim
 climmode
@@ -169,7 +159,6 @@
 conformant
 cong
 const
-constuctors
 contextless
 contourc
 convhull
@@ -196,7 +185,6 @@
 CurrentFigure
 CurrentObject
 currentpoint
-Cuthill
 cxsparse
 Cygwin
 DAE
@@ -224,7 +212,6 @@
 delim
 deltaX
 demi
-Demmel
 DeskJet
 det
 diag
@@ -236,7 +223,6 @@
 displayrange
 dMatrix
 dmperm
-Dobkin
 docstring
 docstrings
 dOmega
@@ -247,11 +233,8 @@
 downarrow
 downdate
 dpi
-Driebeck
 dt
 Dt
-Dulmage
-Durbin
 dx
 dy
 EastOutside
@@ -262,9 +245,7 @@
 eigenvector
 eigenvectors
 eigs
-Ekerdt
 elementwise
-Elfers
 elseif
 emacs
 emptyvalue
@@ -273,7 +254,6 @@
 Endian
 endif
 endofline
-Engle's
 eof
 EOF
 EOLs
@@ -293,7 +273,6 @@
 errordlg
 ErrorHandler
 ESC
-Esmond
 et
 etree
 etreeplot
@@ -317,7 +296,6 @@
 fftpack
 FFTs
 fftw
-Fiedler
 fieldname
 fieldnames
 filename
@@ -336,7 +314,6 @@
 forall
 foregroundcolor
 formfeed
-Forsythe
 Fortran
 fpdf
 fprintf
@@ -356,7 +333,6 @@
 gaminv
 gampdf
 gamrnd
-Gautschi
 gca
 gcbo
 GCC
@@ -385,8 +361,6 @@
 gnuplot
 Gnuplot
 gnuplot's
-Golub
-Gonnet
 goto
 Goto
 gotos
@@ -400,7 +374,6 @@
 GraphicsMagick
 Graymap
 grayscale
-Graz
 griddata
 gswin
 GUIs
@@ -408,16 +381,13 @@
 gz
 gzip
 gzipped
-Hackbusch
 Hadamard
-Haddad
 HandleVisibility
 Hankel
 hanning
 Hanning
 hardcode
 hardcoding
-Hauberg
 HDF
 hdf
 headerlines
@@ -431,11 +401,7 @@
 hggroups
 hh
 HH
-Higham
-Hindmarsh
-Hindmarsh's
 histc
-Hodel
 holomorphic
 Horner's
 horzcat
@@ -444,13 +410,10 @@
 Hotelling's
 HSV
 html
-Hudak
-Huhdanpaa
 hygecdf
 hygeinv
 hygepdf
 hygernd
-Hyndman
 Hypergeometric
 hypergeometric
 IEC
@@ -464,7 +427,6 @@
 Im
 imag
 ImageMagick
-Imenu
 Indices
 indices
 infty
@@ -510,8 +472,6 @@
 jpg
 jvm
 JVM's
-Kac
-Kahan
 kendall
 keybindings
 keypress
@@ -519,10 +479,8 @@
 Kolmogorov
 kolmogorov
 Konrod
-Krishnamurthy
 kron
 kruskal
-Kruskal
 Krylov
 kurtosis
 LabelSpacing
@@ -530,9 +488,7 @@
 Lanzcos
 lapack
 laplace
-Larimore
 LaserJet
-Lauchli
 lceil
 ldiv
 ldivide
@@ -543,10 +499,7 @@
 leftarrow
 Leftrightarrow
 leftrightarrow
-Lehmer
-Lehoucq
 leq
-Levinson
 LF
 lfloor
 li
@@ -568,7 +521,6 @@
 ListSize
 ListString
 literalspacing
-Liu
 LLVM
 LM
 lm
@@ -583,8 +535,6 @@
 lookup
 Lookup
 lookups
-Los
-Lotkin
 Lovato
 lpx
 lr
@@ -600,7 +550,6 @@
 lz
 lzma
 lzw
-Magnus
 Mahalanobis
 makefile
 makefiles
@@ -612,19 +561,14 @@
 markerfacecolor
 markersize
 markerstyle
-Marsaglia
-Maschhoff
 matchcase
 matlab
-Matsumoto
 MaxFunEvals
 maxima
 MaxIntervalCount
 MaxIter
 mcnemar
-McNemar's
 meansq
-Mendelsohn
 menubars
 Mersenne
 meshgrid
@@ -635,7 +579,6 @@
 Metafont
 mex
 mget
-Michelsen
 Microsystems
 MinGW
 minima
@@ -644,7 +587,6 @@
 minval
 MIP
 miscompiled
-Misra
 mkdir
 mkoctfile
 mldivide
@@ -654,8 +596,6 @@
 mmmm
 mmmyy
 mmmyyyy
-Moler
-Montanet
 mpoles
 mpower
 mput
@@ -688,17 +628,13 @@
 ndgrid
 ndims
 ne
-Nelder
 neq
-Neudecker
 Neumann
 NeXT
 NextPlot
 nfev
 nfft
-Ng
 ni
-Nishimura
 NLP
 nnls
 nnz
@@ -741,7 +677,6 @@
 OpenGL
 OpenJDK
 oplus
-Oppenheim
 Ord
 oregonator
 Orthogonalize
@@ -758,7 +693,6 @@
 paperunits
 PaperUnits
 parseparams
-Parter
 pbm
 PBM
 PBMplus
@@ -777,7 +711,6 @@
 pentadiagonal
 periodogram
 perp
-Petzold's
 PGF
 pgm
 PGMRES
@@ -802,7 +735,6 @@
 POSIX
 postorder
 PostScript
-Pothen
 powerset
 pre
 preconditioner
@@ -847,20 +779,17 @@
 qz
 QZ
 radices
-Rajamanickam
 randn
 randperm
 rangle
 ranlib
 ras
-Rawlings
 rceil
 rdivide
 Readline
 readline
 RECT
 recursing
-Redheffer
 reentrant
 regex
 regressor
@@ -895,15 +824,11 @@
 rnd
 roffset
 Rosser
-Rossum
 rpath
 RPMs
 runtime
 sa
-Saad
-Sandia
 SAS
-Schafer
 schar
 Schur
 SCO
@@ -914,7 +839,6 @@
 SelectionMode
 semidefinite
 Sep
-Shampine
 shiftdim
 si
 signum
@@ -930,7 +854,6 @@
 sm
 smirnov
 Smirnov
-Sorensen
 SouthOutside
 sp
 spadesuit
@@ -958,16 +881,12 @@
 sqrtm
 sr
 ss
-Stadlober
 stairstep
-Stallman
 startup
 Startup
 statinfo
 stdnormal
 stdout
-Stegun
-Stepleman
 stepsize
 STFT
 STL
@@ -1033,7 +952,6 @@
 symamd
 symbfact
 symrcm
-Szego
 tcdf
 Tcv
 terminal's
@@ -1047,12 +965,9 @@
 th
 ths
 tif
-Tikhonov
 TikZ
 Timestamp
 tinv
-Tisseur
-Tisseur's
 tmp
 Toeplitz
 tokenExtents
@@ -1076,7 +991,6 @@
 trnd
 truecolor
 TrueColor
-Tsang
 Tukey
 tuples
 Tx
@@ -1145,14 +1059,12 @@
 versa
 vertcat
 vertices
-Villadsen
 voronoi
 Voronoi
 waitbar
 waitbars
 wallis
 warndlg
-Wathen
 WAV
 WayPoints
 wblcdf
@@ -1173,12 +1085,10 @@
 wildcard
 Wildcards
 wildcards
-Wilks
 windowbuttondownfcn
 windowbuttonmotionfcn
 windowbuttonupfcn
 windowstyle
-WinRand
 WIPO
 wireframe
 wp
@@ -1225,7 +1135,6 @@
 YYYY
 yyyymmdd
 yyyymmddTHHMMSS
-Zechner
 Ziggurat
 zlib
 zlim

--- a/doc/interpreter/emacs.txi	Thu Aug 21 18:49:47 2014 +0100
+++ b/doc/interpreter/emacs.txi	Thu Aug 21 15:57:18 2014 -0700
@@ -351,8 +351,8 @@
 @code{font-lock-function-name-face}.
 @end itemize
 
-There is also rudimentary support for Imenu (currently, function names
-can be indexed).
+There is also rudimentary support for @nospell{Imenu} (currently, function
+names can be indexed).
 
 @cindex TAGS
 @cindex Emacs TAGS files

--- a/doc/interpreter/func.txi	Thu Aug 21 18:49:47 2014 +0100
+++ b/doc/interpreter/func.txi	Thu Aug 21 15:57:18 2014 -0700
@@ -1131,7 +1131,7 @@
 which contains the current function.
 
 @item Class constructor
-A function that constuctors a user class as defined in chapter 
+A function that constructs a user class as defined in chapter
 @ref{Object Oriented Programming}.
 
 @item Class method

--- a/doc/interpreter/geometry.txi	Thu Aug 21 18:49:47 2014 +0100
+++ b/doc/interpreter/geometry.txi	Thu Aug 21 15:57:18 2014 -0700
@@ -20,7 +20,7 @@
 @chapter Geometry
 
 Much of the geometry code in Octave is based on the Qhull 
-library@footnote{Barber, C.B., Dobkin, D.P., and Huhdanpaa, H.T., 
+library@footnote{@nospell{Barber, C.B., Dobkin, D.P., and Huhdanpaa, H.T.}, 
 @cite{The Quickhull Algorithm for Convex Hulls}, ACM Trans. on Mathematical 
 Software, 22(4):469--483, Dec 1996, @url{http://www.qhull.org}}.  
 Some of the documentation for Qhull, particularly for the options that 

--- a/doc/interpreter/intro.txi	Thu Aug 21 18:49:47 2014 +0100
+++ b/doc/interpreter/intro.txi	Thu Aug 21 15:57:18 2014 -0700
@@ -334,9 +334,10 @@
 
 @noindent
 The function @code{lsode} uses the Livermore Solver for Ordinary
-Differential Equations, described in A. C. Hindmarsh, @cite{ODEPACK, a
-Systematized Collection of ODE Solvers}, in: Scientific Computing, R. S.
-Stepleman et al. (Eds.), North-Holland, Amsterdam, 1983, pages 55--64.
+Differential Equations, described in @nospell{A. C. Hindmarsh},
+@cite{ODEPACK, a Systematized Collection of ODE Solvers}, in: Scientific
+Computing, @nospell{R. S. Stepleman} et al. (Eds.), North-Holland, Amsterdam,
+1983, pages 55--64.
 
 @subsection Producing Graphical Output
 

--- a/doc/interpreter/linalg.txi	Thu Aug 21 18:49:47 2014 +0100
+++ b/doc/interpreter/linalg.txi	Thu Aug 21 15:57:18 2014 -0700
@@ -21,10 +21,10 @@
 @cindex linear algebra
 
 This chapter documents the linear algebra functions provided in Octave.
-Reference material for many of these functions may be found in Golub and
-Van Loan, @cite{Matrix Computations, 2nd Ed.}, Johns Hopkins, 1989, and
-in the @cite{@sc{lapack} Users' Guide}, SIAM, 1992. The
-@cite{@sc{lapack} Users' Guide} is available at:
+Reference material for many of these functions may be found in
+@nospell{Golub and Van Loan}, @cite{Matrix Computations, 2nd Ed.},
+Johns Hopkins, 1989, and in the @cite{@sc{lapack} Users' Guide}, SIAM, 1992.
+The @cite{@sc{lapack} Users' Guide} is available at:
 @cite{http://www.netlib.org/lapack/lug/}
 
 A common text for engineering courses is @nospell{G. Strang},

--- a/doc/interpreter/numbers.txi	Thu Aug 21 18:49:47 2014 +0100
+++ b/doc/interpreter/numbers.txi	Thu Aug 21 15:57:18 2014 -0700
@@ -311,11 +311,11 @@
 @subsection Empty Matrices
 
 A matrix may have one or both dimensions zero, and operations on empty
-matrices are handled as described by Carl @nospell{de} Boor in @cite{An Empty
-Exercise}, SIGNUM, Volume 25, pages 2-6, 1990 and C. N. Nett and W. M.
-Haddad, in @cite{A System-Theoretic Appropriate Realization of the Empty
-Matrix Concept}, IEEE Transactions on Automatic Control, Volume 38,
-Number 5, May 1993.
+matrices are handled as described by @nospell{Carl de Boor} in
+@cite{An Empty Exercise}, SIGNUM, Volume 25, pages 2-6, 1990 and
+@nospell{C. N. Nett and W. M. Haddad}, in
+@cite{A System-Theoretic Appropriate Realization of the Empty Matrix Concept},
+IEEE Transactions on Automatic Control, Volume 38, Number 5, May 1993.
 @tex
 Briefly, given a scalar $s$, an $m\times n$ matrix $M_{m\times n}$,
 and an $m\times n$ empty matrix $[\,]_{m\times n}$ (with either one or

--- a/doc/interpreter/preface.txi	Thu Aug 21 18:49:47 2014 +0100
+++ b/doc/interpreter/preface.txi	Thu Aug 21 15:57:18 2014 -0700
@@ -24,8 +24,8 @@
 
 Octave was originally intended to be companion software for an
 undergraduate-level textbook on chemical reactor design being written by
-James B. Rawlings of the University of Wisconsin-Madison and John
-G. Ekerdt of the University of Texas.
+@nospell{James B. Rawlings} of the University of Wisconsin-Madison and
+@nospell{John G. Ekerdt} of the University of Texas.
 
 Clearly, Octave is now much more than just another `courseware' package
 with limited utility beyond the classroom.  Although our initial goals
@@ -90,8 +90,8 @@
 @nospell{DE-FG02-04ER25635}.
 
 @item
-Ashok Krishnamurthy, David Hudak, Juan Carlos Chaves, and Stanley
-C. Ahalt of the Ohio Supercomputer Center.
+@nospell{Ashok Krishnamurthy, David Hudak, Juan Carlos Chaves}, and
+@nospell{Stanley C. Ahalt} of the Ohio Supercomputer Center.
 
 @item
 The National Science Foundation, through grant numbers CTS-0105360,
@@ -102,7 +102,7 @@
 Consortium (@url{http://www.che.utexas.edu/twmcc, TWMCC}).
 
 @item
-The Paul A. Elfers Endowed Chair in Chemical Engineering at the
+The @nospell{Paul A. Elfers} Endowed Chair in Chemical Engineering at the
 University of Wisconsin-Madison.
 
 @item
@@ -133,15 +133,16 @@
 Noel Bell, Senior Engineer, Texaco Chemical Company, Austin Texas.
 
 @item
-John A. Turner, Group Leader, Continuum Dynamics @nospell{(CCS-2)}, Los Alamos
-National Laboratory, for registering the @url{octave.org} domain name.
+John A. Turner, Group Leader, Continuum Dynamics @nospell{(CCS-2)},
+@nospell{Los Alamos} National Laboratory, for registering the
+@url{octave.org} domain name.
 
 @item
-James B. Rawlings, Professor, University of Wisconsin-Madison,
+@nospell{James B. Rawlings}, Professor, University of Wisconsin-Madison,
 Department of Chemical and Biological Engineering.
 
 @item
-Richard Stallman, for writing GNU.
+@nospell{Richard Stallman}, for writing GNU.
 @end itemize
 
 This project would not have been possible without the GNU software used

--- a/doc/interpreter/quad.txi	Thu Aug 21 18:49:47 2014 +0100
+++ b/doc/interpreter/quad.txi	Thu Aug 21 15:57:18 2014 -0700
@@ -55,7 +55,7 @@
 Numerical integration using an adaptive Gauss-Konrod rule.
 
 @item quadcc
-Numerical integration using adaptive Clenshaw-Curtis rules.
+Numerical integration using adaptive @nospell{Clenshaw-Curtis} rules.
 
 @item trapz, cumtrapz
 Numerical integration of data using the trapezoidal method.

--- a/doc/interpreter/sparse.txi	Thu Aug 21 18:49:47 2014 +0100
+++ b/doc/interpreter/sparse.txi	Thu Aug 21 15:57:18 2014 -0700
@@ -75,8 +75,8 @@
 of the methods have in common is that they attempt to reduce the complexity
 and storage given a priori knowledge of the particular class of problems
 that will be solved.  A good summary of the available techniques for storing
-sparse matrix is given by Saad @footnote{Y. Saad "SPARSKIT: A basic toolkit
-for sparse matrix computation", 1994,
+sparse matrix is given by @nospell{Saad} @footnote{Y. Saad "SPARSKIT: A basic
+toolkit for sparse matrix computation", 1994,
 @url{http://www-users.cs.umn.edu/~saad/software/SPARSKIT/paper.ps}}.
 With full matrices, knowledge of the point of an element of the matrix
 within the matrix is implied by its position in the computers memory. 
@@ -803,7 +803,7 @@
 matrix solvers can be entirely disabled by using @dfn{spparms} to set
 @code{bandden} to 1 (i.e., @code{spparms ("bandden", 1)}).
 
-The QR@tie{}solver factorizes the problem with a Dulmage-Mendelsohn
+The QR@tie{}solver factorizes the problem with a @nospell{Dulmage-Mendelsohn}
 decomposition, to separate the problem into blocks that can be treated
 as over-determined, multiple well determined blocks, and a final
 over-determined block.  For matrices with blocks of strongly connected

--- a/libinterp/corefcn/colloc.cc	Thu Aug 21 18:49:47 2014 +0100
+++ b/libinterp/corefcn/colloc.cc	Thu Aug 21 15:57:18 2014 -0700
@@ -38,8 +38,8 @@
        "-*- texinfo -*-\n\
 @deftypefn {Built-in Function} {[@var{r}, @var{amat}, @var{bmat}, @var{q}] =} colloc (@var{n}, \"left\", \"right\")\n\
 Compute derivative and integral weight matrices for orthogonal\n\
-collocation using the subroutines given in J. Villadsen and\n\
-M. L. Michelsen, @cite{Solution of Differential Equation Models by\n\
+collocation using the subroutines given in @nospell{J. Villadsen} and\n\
+@nospell{M. L. Michelsen}, @cite{Solution of Differential Equation Models by\n\
 Polynomial Approximation}.\n\
 @end deftypefn")
 {

--- a/libinterp/corefcn/ellipj.cc	Thu Aug 21 18:49:47 2014 +0100
+++ b/libinterp/corefcn/ellipj.cc	Thu Aug 21 15:57:18 2014 -0700
@@ -67,7 +67,7 @@
 return @code{NaN}.\n\
 @end enumerate\n\
 \n\
-Reference: Milton Abramowitz and Irene A Stegun,\n\
+Reference: Milton @nospell{Abramowitz} and Irene A @nospell{Stegun},\n\
 @cite{Handbook of Mathematical Functions}, Chapter 16 (Sections 16.4, 16.13,\n\
 and 16.15), Dover, 1965.\n\
 \n\

--- a/libinterp/corefcn/gammainc.cc	Thu Aug 21 18:49:47 2014 +0100
+++ b/libinterp/corefcn/gammainc.cc	Thu Aug 21 15:57:18 2014 -0700
@@ -57,7 +57,8 @@
 \n\
 @end ifnottex\n\
 with the limiting value of 1 as @var{x} approaches infinity.\n\
-The standard notation is @math{P(a,x)}, e.g., Abramowitz and Stegun (6.5.1).\n\
+The standard notation is @math{P(a,x)}, e.g., @nospell{Abramowitz} and\n\
+@nospell{Stegun} (6.5.1).\n\
 \n\
 If @var{a} is scalar, then @code{gammainc (@var{x}, @var{a})} is returned\n\
 for each element of @var{x} and vice versa.\n\

--- a/libinterp/corefcn/hess.cc	Thu Aug 21 18:49:47 2014 +0100
+++ b/libinterp/corefcn/hess.cc	Thu Aug 21 15:57:18 2014 -0700
@@ -58,8 +58,9 @@
 @end ifnottex\n\
 \n\
 The Hessenberg decomposition is usually used as the first step in an\n\
-eigenvalue computation, but has other applications as well (see Golub,\n\
-Nash, and Van Loan, IEEE Transactions on Automatic Control, 1979).\n\
+eigenvalue computation, but has other applications as well\n\
+(see @nospell{Golub, Nash, and Van Loan},\n\
+IEEE Transactions on Automatic Control, 1979).\n\
 @seealso{eig, chol, lu, qr, qz, schur, svd}\n\
 @end deftypefn")
 {

--- a/libinterp/corefcn/quadcc.cc	Thu Aug 21 18:49:47 2014 +0100
+++ b/libinterp/corefcn/quadcc.cc	Thu Aug 21 15:57:18 2014 -0700
@@ -1492,9 +1492,9 @@
 @deftypefnx {Function File} {@var{q} =} quadcc (@var{f}, @var{a}, @var{b}, @var{tol}, @var{sing})\n\
 @deftypefnx {Function File} {[@var{q}, @var{err}, @var{nr_points}] =} quadcc (@dots{})\n\
 Numerically evaluate the integral of @var{f} from @var{a} to @var{b}\n\
-using the doubly-adaptive Clenshaw-Curtis quadrature described by P. Gonnet\n\
-in @cite{Increasing the Reliability of Adaptive Quadrature Using Explicit\n\
-Interpolants}.\n\
+using the doubly-adaptive @nospell{Clenshaw-Curtis} quadrature described by\n\
+@nospell{P. Gonnet} in @cite{Increasing the Reliability of Adaptive\n\
+Quadrature Using Explicit Interpolants}.\n\
 @var{f} is a function handle, inline function, or string\n\
 containing the name of the function to evaluate.\n\
 The function @var{f} must be vectorized and must return a vector of output\n\
@@ -1540,14 +1540,14 @@
 and, as such, may be less efficient for a smooth or otherwise\n\
 well-behaved integrand than other methods such as @code{quadgk}.\n\
 \n\
-The algorithm uses Clenshaw-Curtis quadrature rules of increasing\n\
+The algorithm uses @nospell{Clenshaw-Curtis} quadrature rules of increasing\n\
 degree in each interval and bisects the interval if either the\n\
 function does not appear to be smooth or a rule of maximum\n\
 degree has been reached.  The error estimate is computed from the\n\
 L2-norm of the difference between two successive interpolations\n\
 of the integrand over the nodes of the respective quadrature rules.\n\
 \n\
-Reference: P. Gonnet, @cite{Increasing the Reliability of Adaptive\n\
+Reference: @nospell{P. Gonnet}, @cite{Increasing the Reliability of Adaptive\n\
 Quadrature Using Explicit Interpolants}, ACM Transactions on\n\
 Mathematical Software, Vol. 37, Issue 3, Article No. 3, 2010.\n\
 @seealso{quad, quadv, quadl, quadgk, trapz, dblquad, triplequad}\n\

--- a/libinterp/corefcn/rand.cc	Thu Aug 21 18:49:47 2014 +0100
+++ b/libinterp/corefcn/rand.cc	Thu Aug 21 15:57:18 2014 -0700
@@ -408,8 +408,8 @@
 vector in Octave's startup files (@pxref{Startup Files}).\n\
 \n\
 To compute the pseudo-random sequence, @code{rand} uses the Mersenne\n\
-Twister with a period of @math{2^{19937}-1} (See M. Matsumoto and\n\
-T. Nishimura,\n\
+Twister with a period of @math{2^{19937}-1} (See\n\
+@nospell{M. Matsumoto and T. Nishimura},\n\
 @cite{Mersenne Twister: A 623-dimensionally equidistributed uniform\n\
 pseudorandom number generator}, ACM Trans. on\n\
 Modeling and Computer Simulation Vol. 8, No. 1, pp. 3-30, January 1998,\n\
@@ -567,14 +567,14 @@
 elements having zero mean and variance one.  The arguments are\n\
 handled the same as the arguments for @code{rand}.\n\
 \n\
-By default, @code{randn} uses the Marsaglia and Tsang ``Ziggurat technique''\n\
-to transform from a uniform to a normal distribution.\n\
+By default, @code{randn} uses the @nospell{Marsaglia and Tsang}\n\
+``Ziggurat technique'' to transform from a uniform to a normal distribution.\n\
 \n\
 The class of the value returned can be controlled by a trailing\n\
 @qcode{\"double\"} or @qcode{\"single\"} argument.  These are the only valid\n\
 classes.\n\
 \n\
-Reference: G. Marsaglia and W.W. Tsang,\n\
+Reference: @nospell{G. Marsaglia and W.W. Tsang},\n\
 @cite{Ziggurat Method for Generating Random Variables},\n\
 J. Statistical Software, vol 5, 2000,\n\
 @url{http://www.jstatsoft.org/v05/i08/}\n\
@@ -638,14 +638,14 @@
 Return a matrix with exponentially distributed random elements.  The\n\
 arguments are handled the same as the arguments for @code{rand}.\n\
 \n\
-By default, @code{randn} uses the Marsaglia and Tsang ``Ziggurat technique''\n\
-to transform from a uniform to an exponential distribution.\n\
+By default, @code{randn} uses the @nospell{Marsaglia and Tsang}\n\
+``Ziggurat technique'' to transform from a uniform to a normal distribution.\n\
 \n\
 The class of the value returned can be controlled by a trailing\n\
 @qcode{\"double\"} or @qcode{\"single\"} argument.  These are the only valid\n\
 classes.\n\
 \n\
-Reference: G. Marsaglia and W.W. Tsang,\n\
+Reference: @nospell{G. Marsaglia and W.W. Tsang},\n\
 @cite{Ziggurat Method for Generating Random Variables},\n\
 J. Statistical Software, vol 5, 2000,\n\
 @url{http://www.jstatsoft.org/v05/i08/}\n\
@@ -1003,17 +1003,17 @@
 Cambridge University Press, 1992.\n\
 \n\
 @item For matrix @var{l} @leq{} 10, use inversion method.[2]\n\
-E. Stadlober, et al., WinRand source code, available via FTP.\n\
+@nospell{E. Stadlober, et al., WinRand source code}, available via FTP.\n\
 \n\
 @item For matrix @var{l} > 10, use patchwork rejection method.\n\
-E. Stadlober, et al., WinRand source code, available via FTP, or\n\
-H. Zechner, @cite{Efficient sampling from continuous and discrete\n\
+@nospell{E. Stadlober, et al., WinRand source code}, available via FTP, or\n\
+@nospell{H. Zechner}, @cite{Efficient sampling from continuous and discrete\n\
 unimodal distributions}, Doctoral Dissertation, 156pp., Technical\n\
-University Graz, Austria, 1994.\n\
+University @nospell{Graz}, Austria, 1994.\n\
 \n\
 @item For @var{l} > 1e8, use normal approximation.\n\
-L. Montanet, et al., @cite{Review of Particle Properties}, Physical Review\n\
-D 50 p1284, 1994.\n\
+@nospell{L. Montanet}, et al., @cite{Review of Particle Properties},\n\
+Physical Review D 50 p1284, 1994.\n\
 @end table\n\
 \n\
 The class of the value returned can be controlled by a trailing\n\

--- a/libinterp/corefcn/sqrtm.cc	Thu Aug 21 18:49:47 2014 +0100
+++ b/libinterp/corefcn/sqrtm.cc	Thu Aug 21 15:57:18 2014 -0700
@@ -206,7 +206,7 @@
 @deftypefnx {Built-in Function} {[@var{s}, @var{error_estimate}] =} sqrtm (@var{A})\n\
 Compute the matrix square root of the square matrix @var{A}.\n\
 \n\
-Ref: N.J. Higham.  @cite{A New sqrtm for @sc{matlab}}.  Numerical\n\
+Ref: @nospell{N.J. Higham}.  @cite{A New sqrtm for @sc{matlab}}.  Numerical\n\
 Analysis Report No. 336, Manchester @nospell{Centre} for Computational\n\
 Mathematics, Manchester, England, January 1999.\n\
 @seealso{expm, logm}\n\

--- a/libinterp/dldfcn/ccolamd.cc	Thu Aug 21 18:49:47 2014 +0100
+++ b/libinterp/dldfcn/ccolamd.cc	Thu Aug 21 15:57:18 2014 -0700
@@ -132,11 +132,12 @@
 or out-of-order row indices.  @code{@var{stats}(8 : 20)} is always zero in\n\
 the current version of @sc{ccolamd} (reserved for future use).\n\
 \n\
-The authors of the code itself are S. Larimore, T. Davis (Univ. of Florida)\n\
-and S. Rajamanickam in collaboration with J. Bilbert and E. Ng.  Supported\n\
-by the National Science Foundation\n\
-@nospell{(DMS-9504974, DMS-9803599, CCR-0203270)}, and a grant from Sandia\n\
-National Lab.  See @url{http://www.cise.ufl.edu/research/sparse} for\n\
+The authors of the code itself are @nospell{S. Larimore, T. Davis}\n\
+(Univ. of Florida) and @nospell{S. Rajamanickam} in collaboration with\n\
+@nospell{J. Bilbert and E. Ng}.  Supported by the National Science Foundation\n\
+@nospell{(DMS-9504974, DMS-9803599, CCR-0203270)}, and a grant from\n\
+@nospell{Sandia} National Lab.\n\
+See @url{http://www.cise.ufl.edu/research/sparse} for\n\
 ccolamd, csymamd, amd, colamd, symamd, and other related orderings.\n\
 @seealso{colamd, csymamd}\n\
 @end deftypefn")
@@ -389,11 +390,12 @@
 or out-of-order row indices.  @code{@var{stats}(8:20)} is always zero in\n\
 the current version of @sc{ccolamd} (reserved for future use).\n\
 \n\
-The authors of the code itself are S. Larimore, T. Davis (Uni of Florida)\n\
-and S. Rajamanickam in collaboration with J. Bilbert and E. Ng.  Supported\n\
-by the National Science Foundation\n\
-@nospell{(DMS-9504974, DMS-9803599, CCR-0203270)}, and a grant from Sandia\n\
-National Lab.  See @url{http://www.cise.ufl.edu/research/sparse} for\n\
+The authors of the code itself are @nospell{S. Larimore, T. Davis}\n\
+(Univ. of Florida) and @nospell{S. Rajamanickam} in collaboration with\n\
+@nospell{J. Bilbert and E. Ng}.  Supported by the National Science Foundation\n\
+@nospell{(DMS-9504974, DMS-9803599, CCR-0203270)}, and a grant from\n\
+@nospell{Sandia} National Lab.\n\
+See @url{http://www.cise.ufl.edu/research/sparse} for\n\
 ccolamd, csymamd, amd, colamd, symamd, and other related orderings.\n\
 @seealso{symamd, ccolamd}\n\
 @end deftypefn")

--- a/libinterp/dldfcn/colamd.cc	Thu Aug 21 18:49:47 2014 +0100
+++ b/libinterp/dldfcn/colamd.cc	Thu Aug 21 15:57:18 2014 -0700
@@ -270,10 +270,9 @@
 \n\
 The ordering is followed by a column elimination tree post-ordering.\n\
 \n\
-The authors of the code itself are Stefan I. Larimore and Timothy A.\n\
-Davis @email{davis@@cise.ufl.edu}, University of Florida.  The algorithm was\n\
-developed in collaboration with John Gilbert, Xerox PARC, and Esmond\n\
-Ng, Oak Ridge National Laboratory.  (see\n\
+The authors of the code itself are @nospell{Stefan I. Larimore} and\n\
+@nospell{Timothy A. Davis @email{davis@@cise.ufl.edu}}, University of Florida.  The algorithm was developed in collaboration with @nospell{John Gilbert},\n\
+Xerox PARC, and @nospell{Esmond Ng}, Oak Ridge National Laboratory.  (see\n\
 @url{http://www.cise.ufl.edu/research/sparse/colamd})\n\
 @seealso{colperm, symamd, ccolamd}\n\
 @end deftypefn")
@@ -506,10 +505,9 @@
 \n\
 The ordering is followed by a column elimination tree post-ordering.\n\
 \n\
-The authors of the code itself are Stefan I. Larimore and Timothy A.\n\
-Davis @email{davis@@cise.ufl.edu}, University of Florida.  The algorithm was\n\
-developed in collaboration with John Gilbert, Xerox PARC, and Esmond\n\
-Ng, Oak Ridge National Laboratory.  (see\n\
+The authors of the code itself are @nospell{Stefan I. Larimore} and\n\
+@nospell{Timothy A. Davis @email{davis@@cise.ufl.edu}}, University of Florida.  The algorithm was developed in collaboration with @nospell{John Gilbert},\n\
+Xerox PARC, and @nospell{Esmond Ng}, Oak Ridge National Laboratory.  (see\n\
 @url{http://www.cise.ufl.edu/research/sparse/colamd})\n\
 @seealso{colperm, colamd}\n\
 @end deftypefn")

--- a/libinterp/dldfcn/dmperm.cc	Thu Aug 21 18:49:47 2014 +0100
+++ b/libinterp/dldfcn/dmperm.cc	Thu Aug 21 15:57:18 2014 -0700
@@ -136,8 +136,10 @@
 @deftypefn  {Loadable Function} {@var{p} =} dmperm (@var{S})\n\
 @deftypefnx {Loadable Function} {[@var{p}, @var{q}, @var{r}, @var{S}] =} dmperm (@var{S})\n\
 \n\
-@cindex Dulmage-Mendelsohn decomposition\n\
-Perform a Dulmage-Mendelsohn permutation of the sparse matrix @var{S}.\n\
+@cindex @nospell{Dulmage-Mendelsohn} decomposition\n\
+Perform a @nospell{Dulmage-Mendelsohn} permutation of the sparse matrix\n\
+@var{S}.\n\
+\n\
 With a single output argument @code{dmperm} performs the row permutations\n\
 @var{p} such that @code{@var{S}(@var{p},:)} has no zero elements on the\n\
 diagonal.\n\
@@ -147,9 +149,9 @@
 triangular form.  The values of @var{r} and @var{S} define the boundaries\n\
 of the blocks.  If @var{S} is square then @code{@var{r} == @var{S}}.\n\
 \n\
-The method used is described in: A. Pothen & C.-J. Fan. @cite{Computing the\n\
-Block Triangular Form of a Sparse Matrix}. ACM Trans. Math. Software,\n\
-16(4):303-324, 1990.\n\
+The method used is described in: @nospell{A. Pothen & C.-J. Fan.}\n\
+@cite{Computing the Block Triangular Form of a Sparse Matrix}.\n\
+ACM Trans. Math. Software, 16(4):303-324, 1990.\n\
 @seealso{colamd, ccolamd}\n\
 @end deftypefn")
 {
@@ -194,8 +196,8 @@
 \n\
 Calculate the structural rank of the sparse matrix @var{S}.  Note that\n\
 only the structure of the matrix is used in this calculation based on\n\
-a Dulmage-Mendelsohn permutation to block triangular form.  As such the\n\
-numerical rank of the matrix @var{S} is bounded by\n\
+a @nospell{Dulmage-Mendelsohn} permutation to block triangular form.  As\n\
+such the numerical rank of the matrix @var{S} is bounded by\n\
 @code{sprank (@var{S}) >= rank (@var{S})}.  Ignoring floating point errors\n\
 @code{sprank (@var{S}) == rank (@var{S})}.\n\
 @seealso{dmperm}\n\

--- a/libinterp/dldfcn/symrcm.cc	Thu Aug 21 18:49:47 2014 +0100
+++ b/libinterp/dldfcn/symrcm.cc	Thu Aug 21 15:57:18 2014 -0700
@@ -414,7 +414,7 @@
 DEFUN_DLD (symrcm, args, ,
            "-*- texinfo -*-\n\
 @deftypefn {Loadable Function} {@var{p} =} symrcm (@var{S})\n\
-Return the symmetric reverse Cuthill-McKee permutation of @var{S}.\n\
+Return the symmetric reverse @nospell{Cuthill-McKee} permutation of @var{S}.\n\
 @var{p} is a permutation vector such that\n\
 @code{@var{S}(@var{p}, @var{p})} tends to have its diagonal elements\n\
 closer to the diagonal than @var{S}.  This is a good preordering for LU\n\
@@ -425,11 +425,11 @@
 bandwidth minimization problem.  The implementation is based in the\n\
 descriptions found in\n\
 \n\
-E. Cuthill, J. McKee. @cite{Reducing the Bandwidth of Sparse Symmetric\n\
-Matrices}. Proceedings of the 24th ACM National Conference, 157--172\n\
+@nospell{E. Cuthill, J. McKee}. @cite{Reducing the Bandwidth of Sparse\n\
+Symmetric Matrices}. Proceedings of the 24th ACM National Conference, 157--172\n\
 1969, Brandon Press, New Jersey.\n\
 \n\
-A. George, J.W.H. Liu. @cite{Computer Solution of Large Sparse\n\
+@nospell{A. George, J.W.H. Liu}. @cite{Computer Solution of Large Sparse\n\
 Positive Definite Systems}, Prentice Hall Series in Computational\n\
 Mathematics, ISBN 0-13-165274-5, 1981.\n\
 \n\

--- a/scripts/general/quadgk.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/general/quadgk.m	Thu Aug 21 15:57:18 2014 -0700
@@ -27,7 +27,7 @@
 ## using adaptive Gauss-Konrod quadrature.
 ## @var{f} is a function handle, inline function, or string
 ## containing the name of the function to evaluate.
-## The formulation is based on a proposal by L.F. Shampine,
+## The formulation is based on a proposal by @nospell{L.F. Shampine},
 ## @cite{"Vectorized adaptive quadrature in @sc{matlab}", Journal of
 ## Computational and Applied Mathematics, pp131-140, Vol 211, Issue 2,
 ## Feb 2008} where all function evaluations at an iteration are

--- a/scripts/general/quadl.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/general/quadl.m	Thu Aug 21 15:57:18 2014 -0700
@@ -45,7 +45,7 @@
 ## @var{f}.  To use default values for @var{tol} and @var{trace}, one may pass
 ## empty matrices ([]).
 ##
-## Reference: W. Gander and W. Gautschi, @cite{Adaptive Quadrature -
+## Reference: @nospell{W. Gander and W. Gautschi}, @cite{Adaptive Quadrature -
 ## Revisited}, BIT Vol. 40, No. 1, March 2000, pp. 84--101.
 ## @url{http://www.inf.ethz.ch/personal/gander/}
 ## @seealso{quad, quadv, quadgk, quadcc, trapz, dblquad, triplequad}

--- a/scripts/linear-algebra/commutation_matrix.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/linear-algebra/commutation_matrix.m	Thu Aug 21 15:57:18 2014 -0700
@@ -63,8 +63,8 @@
 ## @end ifnottex
 ##  is returned.
 ##
-## See Magnus and Neudecker (1988), @cite{Matrix Differential Calculus with
-## Applications in Statistics and Econometrics.}
+## See @nospell{Magnus and Neudecker} (1988), @cite{Matrix Differential
+## Calculus with Applications in Statistics and Econometrics.}
 ## @end deftypefn
 
 ## Author: KH <Kurt.Hornik@wu-wien.ac.at>

--- a/scripts/linear-algebra/condest.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/linear-algebra/condest.m	Thu Aug 21 15:57:18 2014 -0700
@@ -59,13 +59,13 @@
 ##
 ## @itemize
 ## @item
-## N.J. Higham and F. Tisseur, @cite{A Block Algorithm
+## @nospell{N.J. Higham and F. Tisseur}, @cite{A Block Algorithm
 ## for Matrix 1-Norm Estimation, with an Application to 1-Norm
 ## Pseudospectra}. SIMAX vol 21, no 4, pp 1185-1201.
 ## @url{http://dx.doi.org/10.1137/S0895479899356080}
 ##
 ## @item
-## N.J. Higham and F. Tisseur, @cite{A Block Algorithm
+## @nospell{N.J. Higham and F. Tisseur}, @cite{A Block Algorithm
 ## for Matrix 1-Norm Estimation, with an Application to 1-Norm
 ## Pseudospectra}. @url{http://citeseer.ist.psu.edu/223007.html}
 ## @end itemize

--- a/scripts/linear-algebra/duplication_matrix.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/linear-algebra/duplication_matrix.m	Thu Aug 21 15:57:18 2014 -0700
@@ -54,8 +54,8 @@
 ##  @math{A}.
 ## @end ifnottex
 ##
-## See Magnus and Neudecker (1988), Matrix differential calculus with
-## applications in statistics and econometrics.
+## See @nospell{Magnus and Neudecker} (1988), @cite{Matrix Differential
+## Calculus with Applications in Statistics and Econometrics.}
 ## @end deftypefn
 
 ## Author: KH <Kurt.Hornik@wu-wien.ac.at>

--- a/scripts/linear-algebra/expm.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/linear-algebra/expm.m	Thu Aug 21 15:57:18 2014 -0700
@@ -33,8 +33,8 @@
 ##
 ## @end ifnottex
 ## The Taylor series is @emph{not} the way to compute the matrix
-## exponential; see Moler and Van Loan, @cite{Nineteen Dubious Ways to
-## Compute the Exponential of a Matrix}, SIAM Review, 1978.  This routine
+## exponential; see @nospell{Moler and Van Loan}, @cite{Nineteen Dubious Ways
+## to Compute the Exponential of a Matrix}, SIAM Review, 1978.  This routine
 ## uses Ward's diagonal Pad@'e approximation method with three step
 ## preconditioning (SIAM Journal on Numerical Analysis, 1977).  Diagonal
 ## Pad@'e approximations are rational polynomials of matrices

--- a/scripts/linear-algebra/housh.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/linear-algebra/housh.m	Thu Aug 21 15:57:18 2014 -0700
@@ -43,7 +43,7 @@
 ## @end table
 ##
 ## @noindent
-## Outputs (see Golub and Van Loan):
+## Outputs (see @nospell{Golub and Van Loan}):
 ##
 ## @table @var
 ## @item beta

--- a/scripts/linear-algebra/krylov.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/linear-algebra/krylov.m	Thu Aug 21 15:57:18 2014 -0700
@@ -49,9 +49,9 @@
 ## If the optional parameter @var{pflg} is nonzero, row pivoting is used
 ## to improve numerical behavior.  The default value is 0.
 ##
-## Reference: A. Hodel, P. Misra, @cite{Partial Pivoting in the Computation of
-## Krylov Subspaces of Large Sparse Systems}, Proceedings of the 42nd IEEE
-## Conference on Decision and Control, December 2003.
+## Reference: @nospell{A. Hodel, P. Misra}, @cite{Partial Pivoting in the
+## Computation of Krylov Subspaces of Large Sparse Systems}, Proceedings of
+## the 42nd IEEE Conference on Decision and Control, December 2003.
 ## @end deftypefn
 
 ## Author: A. Scottedward Hodel <a.s.hodel@eng.auburn.edu>

--- a/scripts/linear-algebra/onenormest.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/linear-algebra/onenormest.m	Thu Aug 21 15:57:18 2014 -0700
@@ -20,7 +20,7 @@
 ## @deftypefn  {Function File} {[@var{est}, @var{v}, @var{w}, @var{iter}] =} onenormest (@var{A}, @var{t})
 ## @deftypefnx {Function File} {[@var{est}, @var{v}, @var{w}, @var{iter}] =} onenormest (@var{apply}, @var{apply_t}, @var{n}, @var{t})
 ##
-## Apply Higham and Tisseur's randomized block 1-norm estimator to
+## Apply @nospell{Higham and Tisseur's} randomized block 1-norm estimator to
 ## matrix @var{A} using @var{t} test vectors.  If @var{t} exceeds 5, then
 ## only 5 test vectors are used.
 ##
@@ -41,13 +41,13 @@
 ##
 ## @itemize
 ## @item
-## N.J. Higham and F. Tisseur, @cite{A Block Algorithm
+## @nospell{N.J. Higham and F. Tisseur}, @cite{A Block Algorithm
 ## for Matrix 1-Norm Estimation, with an Application to 1-Norm
 ## Pseudospectra}. SIMAX vol 21, no 4, pp 1185-1201.
 ## @url{http://dx.doi.org/10.1137/S0895479899356080}
 ##
 ## @item
-## N.J. Higham and F. Tisseur, @cite{A Block Algorithm
+## @nospell{N.J. Higham and F. Tisseur}, @cite{A Block Algorithm
 ## for Matrix 1-Norm Estimation, with an Application to 1-Norm
 ## Pseudospectra}. @url{http://citeseer.ist.psu.edu/223007.html}
 ## @end itemize

--- a/scripts/linear-algebra/qzhess.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/linear-algebra/qzhess.m	Thu Aug 21 15:57:18 2014 -0700
@@ -35,9 +35,9 @@
 ## @end example
 ##
 ## The Hessenberg-triangular decomposition is the first step in
-## Moler and Stewart's QZ@tie{}decomposition algorithm.
+## @nospell{Moler and Stewart's} QZ@tie{}decomposition algorithm.
 ##
-## Algorithm taken from Golub and Van Loan,
+## Algorithm taken from @nospell{Golub and Van Loan},
 ## @cite{Matrix Computations, 2nd edition}.
 ## 
 ## @seealso{lu, chol, hess, qr, qz, schur, svd}

--- a/scripts/optimization/fminsearch.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/optimization/fminsearch.m	Thu Aug 21 15:57:18 2014 -0700
@@ -24,9 +24,9 @@
 ##
 ## Find a value of @var{x} which minimizes the function @var{fun}.
 ## The search begins at the point @var{x0} and iterates using the
-## Nelder & Mead Simplex algorithm (a derivative-free method).  This algorithm
-## is better-suited to functions which have discontinuities or for which
-## a gradient-based search such as @code{fminunc} fails.
+## @nospell{Nelder & Mead} Simplex algorithm (a derivative-free method).  This
+## algorithm is better-suited to functions which have discontinuities or for
+## which a gradient-based search such as @code{fminunc} fails.
 ##
 ## Options for the search are provided in the parameter @var{options} using 
 ## the function @code{optimset}.  Currently, @code{fminsearch} accepts the

--- a/scripts/optimization/glpk.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/optimization/glpk.m	Thu Aug 21 15:57:18 2014 -0700
@@ -238,7 +238,7 @@
 ## Most fractional variable.
 ##
 ## @item 4 (@w{@code{GLP_BR_DTH}})
-## Heuristic by Driebeck and Tomlin.
+## Heuristic by @nospell{Driebeck and Tomlin}.
 ##
 ## @item 5 (@w{@code{GLP_BR_PCH}})
 ## Hybrid @nospell{pseudocost} heuristic.

--- a/scripts/signal/arch_fit.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/signal/arch_fit.m	Thu Aug 21 15:57:18 2014 -0700
@@ -19,7 +19,7 @@
 ## -*- texinfo -*-
 ## @deftypefn {Function File} {[@var{a}, @var{b}] =} arch_fit (@var{y}, @var{x}, @var{p}, @var{iter}, @var{gamma}, @var{a0}, @var{b0})
 ## Fit an ARCH regression model to the time series @var{y} using the
-## scoring algorithm in Engle's original ARCH paper.  The model is
+## scoring algorithm in @nospell{Engle's} original ARCH paper.  The model is
 ##
 ## @example
 ## @group

--- a/scripts/signal/bartlett.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/signal/bartlett.m	Thu Aug 21 15:57:18 2014 -0700
@@ -21,8 +21,9 @@
 ## Return the filter coefficients of a Bartlett (triangular) window of
 ## length @var{m}.
 ##
-## For a definition of the Bartlett window, see e.g., A. V. Oppenheim &
-## R. W. Schafer, @cite{Discrete-Time Signal Processing}.
+## For a definition of the Bartlett window, see e.g.,
+## @nospell{A.V. Oppenheim & R. W. Schafer},
+## @cite{Discrete-Time Signal Processing}.
 ## @end deftypefn
 
 ## Author: AW <Andreas.Weingessel@ci.tuwien.ac.at>

--- a/scripts/signal/blackman.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/signal/blackman.m	Thu Aug 21 15:57:18 2014 -0700
@@ -20,8 +20,9 @@
 ## @deftypefn {Function File} {} blackman (@var{m})
 ## Return the filter coefficients of a Blackman window of length @var{m}.
 ##
-## For a definition of the Blackman window, see e.g., A. V. Oppenheim &
-## R. W. Schafer, @cite{Discrete-Time Signal Processing}.
+## For a definition of the Blackman window, see e.g.,
+## @nospell{A.V. Oppenheim & R. W. Schafer},
+## @cite{Discrete-Time Signal Processing}.
 ## @end deftypefn
 
 ## Author: AW <Andreas.Weingessel@ci.tuwien.ac.at>

--- a/scripts/signal/diffpara.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/signal/diffpara.m	Thu Aug 21 15:57:18 2014 -0700
@@ -32,7 +32,7 @@
 ## described above is returned in @var{dd}.  The value of @var{d} is
 ## simply the mean of @var{dd}.
 ##
-## Reference: P.J. Brockwell & R.A. Davis. @cite{Time Series:
+## Reference: @nospell{P.J. Brockwell & R.A. Davis}. @cite{Time Series:
 ## Theory and Methods}. Springer 1987.
 ## @end deftypefn
 

--- a/scripts/signal/durbinlevinson.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/signal/durbinlevinson.m	Thu Aug 21 15:57:18 2014 -0700
@@ -18,7 +18,7 @@
 
 ## -*- texinfo -*-
 ## @deftypefn {Function File} {} durbinlevinson (@var{c}, @var{oldphi}, @var{oldv})
-## Perform one step of the Durbin-Levinson algorithm.
+## Perform one step of the @nospell{Durbin-Levinson} algorithm.
 ##
 ## The vector @var{c} specifies the autocovariances @code{[gamma_0, @dots{},
 ## gamma_t]} from lag 0 to @var{t}, @var{oldphi} specifies the

--- a/scripts/signal/hamming.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/signal/hamming.m	Thu Aug 21 15:57:18 2014 -0700
@@ -20,8 +20,9 @@
 ## @deftypefn {Function File} {} hamming (@var{m})
 ## Return the filter coefficients of a Hamming window of length @var{m}.
 ##
-## For a definition of the Hamming window, see e.g., A. V. Oppenheim &
-## R. W. Schafer, @cite{Discrete-Time Signal Processing}.
+## For a definition of the Hamming window, see e.g.,
+## @nospell{A.V. Oppenheim & R. W. Schafer},
+## @cite{Discrete-Time Signal Processing}.
 ## @end deftypefn
 
 ## Author: AW <Andreas.Weingessel@ci.tuwien.ac.at>

--- a/scripts/signal/hanning.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/signal/hanning.m	Thu Aug 21 15:57:18 2014 -0700
@@ -20,8 +20,9 @@
 ## @deftypefn {Function File} {} hanning (@var{m})
 ## Return the filter coefficients of a Hanning window of length @var{m}.
 ##
-## For a definition of this window type, see e.g., A. V. Oppenheim &
-## R. W. Schafer, @cite{Discrete-Time Signal Processing}.
+## For a definition of the Hanning window, see e.g.,
+## @nospell{A.V. Oppenheim & R. W. Schafer},
+## @cite{Discrete-Time Signal Processing}.
 ## @end deftypefn
 
 ## Author: AW <Andreas.Weingessel@ci.tuwien.ac.at>

--- a/scripts/sparse/eigs.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/sparse/eigs.m	Thu Aug 21 15:57:18 2014 -0700
@@ -183,9 +183,9 @@
 ## of the convergence.  If @var{flag} is 0 then all eigenvalues have converged.
 ## Any other value indicates a failure to converge.
 ## 
-## This function is based on the @sc{arpack} package, written by R. Lehoucq,
-## K. Maschhoff, D. Sorensen, and C. Yang.  For more information see
-## @url{http://www.caam.rice.edu/software/ARPACK/}.
+## This function is based on the @sc{arpack} package, written by
+## @nospell{R. Lehoucq, K. Maschhoff, D. Sorensen, and C. Yang}.  For more
+## information see @url{http://www.caam.rice.edu/software/ARPACK/}.
 ## 
 ## @seealso{eig, svds}
 ## @end deftypefn

--- a/scripts/sparse/pcg.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/sparse/pcg.m	Thu Aug 21 15:57:18 2014 -0700
@@ -203,7 +203,7 @@
 ## SIAM, 1995. (the base PCG algorithm)
 ##
 ## @item
-## Y. Saad, @cite{Iterative Methods for Sparse Linear Systems}, 
+## @nospell{Y. Saad}, @cite{Iterative Methods for Sparse Linear Systems}, 
 ## @nospell{PWS} 1996. (condition number estimate from PCG)
 ## Revised version of this book is available online at
 ## @url{http://www-users.cs.umn.edu/~saad/books.html}

--- a/scripts/sparse/pcr.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/sparse/pcr.m	Thu Aug 21 15:57:18 2014 -0700
@@ -162,8 +162,8 @@
 ##
 ## References:
 ##
-##      [1] W. Hackbusch, @cite{Iterative Solution of Large Sparse Systems of
-##      Equations}, section 9.5.4; Springer, 1994
+## [1] @nospell{W. Hackbusch}, @cite{Iterative Solution of Large Sparse
+## Systems of Equations}, section 9.5.4; Springer, 1994
 ##
 ## @seealso{sparse, pcg}
 ## @end deftypefn

--- a/scripts/specfun/ellipke.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/specfun/ellipke.m	Thu Aug 21 15:57:18 2014 -0700
@@ -33,7 +33,7 @@
 ## Called with only one output, elliptic integrals of the first kind are
 ## returned.
 ##
-## Reference: Milton Abramowitz and Irene A. Stegun,
+## Reference: Milton @nospell{Abramowitz} and Irene A. @nospell{Stegun},
 ## @cite{Handbook of Mathematical Functions}, Chapter 17, Dover, 1965.
 ## @seealso{ellipj}
 ## @end deftypefn

--- a/scripts/special-matrix/gallery.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/special-matrix/gallery.m	Thu Aug 21 15:57:18 2014 -0700
@@ -83,7 +83,7 @@
 ## @deftypefn  {Function File} {[@var{c}, @var{d}, @var{e}] =} gallery ("dorr", @var{n})
 ## @deftypefnx {Function File} {[@var{c}, @var{d}, @var{e}] =} gallery ("dorr", @var{n}, @var{theta})
 ## @deftypefnx {Function File} {@var{a} =} gallery ("dorr", @dots{})
-## Create a diagonally dominant, ill conditioned, tridiagonal matrix.
+## Create a diagonally dominant, ill-conditioned, tridiagonal matrix.
 ##
 ## @end deftypefn
 ##
@@ -94,20 +94,20 @@
 ## @end deftypefn
 ##
 ## @deftypefn {Function File} {@var{a} =} gallery ("fiedler", @var{c})
-## Create a symmetric Fiedler matrix.
+## Create a symmetric @nospell{Fiedler} matrix.
 ##
 ## @end deftypefn
 ##
 ## @deftypefn  {Function File} {@var{a} =} gallery ("forsythe", @var{n})
 ## @deftypefnx {Function File} {@var{a} =} gallery ("forsythe", @var{n}, @var{alpha})
 ## @deftypefnx {Function File} {@var{a} =} gallery ("forsythe", @var{n}, @var{alpha}, @var{lambda})
-## Create a Forsythe matrix (a perturbed Jordan block).
+## Create a @nospell{Forsythe} matrix (a perturbed Jordan block).
 ##
 ## @end deftypefn
 ##
 ## @deftypefn  {Function File} {@var{f} =} gallery ("frank", @var{n})
 ## @deftypefnx {Function File} {@var{f} =} gallery ("frank", @var{n}, @var{k})
-## Create a Frank matrix (ill conditioned eigenvalues).
+## Create a Frank matrix (ill-conditioned eigenvalues).
 ##
 ## @end deftypefn
 ##
@@ -194,13 +194,13 @@
 ## @deftypefn  {Function File} {@var{u} =} gallery ("kahan", @var{n})
 ## @deftypefnx {Function File} {@var{u} =} gallery ("kahan", @var{n}, @var{theta})
 ## @deftypefnx {Function File} {@var{u} =} gallery ("kahan", @var{n}, @var{theta}, @var{pert})
-## Create a Kahan matrix (upper trapezoidal).
+## Create a @nospell{Kahan} matrix (upper trapezoidal).
 ##
 ## @end deftypefn
 ##
 ## @deftypefn  {Function File} {@var{a} =} gallery ("kms", @var{n})
 ## @deftypefnx {Function File} {@var{a} =} gallery ("kms", @var{n}, @var{rho})
-## Create a Kac-Murdock-Szego Toeplitz matrix.
+## Create a @nospell{Kac-Murdock-Szego} Toeplitz matrix.
 ##
 ## @end deftypefn
 ##
@@ -213,12 +213,12 @@
 ##
 ## @deftypefn  {Function File} {@var{a} =} gallery ("lauchli", @var{n})
 ## @deftypefnx {Function File} {@var{a} =} gallery ("lauchli", @var{n}, @var{mu})
-## Create a Lauchli matrix (rectangular).
+## Create a @nospell{Lauchli} matrix (rectangular).
 ##
 ## @end deftypefn
 ##
 ## @deftypefn {Function File} {@var{a} =} gallery ("lehmer", @var{n})
-## Create a Lehmer matrix (symmetric positive definite).
+## Create a @nospell{Lehmer} matrix (symmetric positive definite).
 ##
 ## @end deftypefn
 ##
@@ -228,7 +228,7 @@
 ## @end deftypefn
 ##
 ## @deftypefn {Function File} {@var{a} =} gallery ("lotkin", @var{n})
-## Create a Lotkin matrix.
+## Create a @nospell{Lotkin} matrix.
 ##
 ## @end deftypefn
 ##
@@ -239,7 +239,7 @@
 ##
 ## @deftypefn  {Function File} {@var{a} =} gallery ("moler", @var{n})
 ## @deftypefnx {Function File} {@var{a} =} gallery ("moler", @var{n}, @var{alpha})
-## Create a Moler matrix (symmetric positive definite).
+## Create a @nospell{Moler} matrix (symmetric positive definite).
 ##
 ## @end deftypefn
 ##
@@ -274,7 +274,8 @@
 ## @end deftypefn
 ##
 ## @deftypefn {Function File} {@var{a} =} gallery ("parter", @var{n})
-## Create a Parter matrix (a Toeplitz matrix with singular values near pi).
+## Create a @nospell{Parter} matrix (a Toeplitz matrix with singular values
+## near pi).
 ##
 ## @end deftypefn
 ##
@@ -316,8 +317,8 @@
 ## @end deftypefn
 ##
 ## @deftypefn {Function File} {@var{a} =} gallery ("redheff", @var{n})
-## Create a zero and ones matrix of Redheffer associated with the Riemann
-## hypothesis.
+## Create a zero and ones matrix of @nospell{Redheffer} associated with the
+## Riemann hypothesis.
 ##
 ## @end deftypefn
 ##
@@ -365,7 +366,8 @@
 ## @deftypefn  {Function File} {@var{t} =} gallery ("triw", @var{n})
 ## @deftypefnx {Function File} {@var{t} =} gallery ("triw", @var{n}, @var{alpha})
 ## @deftypefnx {Function File} {@var{t} =} gallery ("triw", @var{n}, @var{alpha}, @var{k})
-## Create an upper triangular matrix discussed by Kahan, Golub and Wilkinson.
+## Create an upper triangular matrix discussed by
+## @nospell{Kahan, Golub, and Wilkinson}.
 ##
 ## @end deftypefn
 ##
@@ -390,7 +392,7 @@
 ##
 ## @deftypefn  {Function File} {@var{a} =} gallery ("wathen", @var{nx}, @var{ny})
 ## @deftypefnx {Function File} {@var{a} =} gallery ("wathen", @var{nx}, @var{ny}, @var{k})
-## Create the Wathen matrix.
+## Create the @nospell{Wathen} matrix.
 ##
 ## @end deftypefn
 ##

--- a/scripts/special-matrix/invhilb.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/special-matrix/invhilb.m	Thu Aug 21 15:57:18 2014 -0700
@@ -63,7 +63,7 @@
 ## The validity of this formula can easily be checked by expanding
 ## the binomial coefficients in both formulas as factorials.  It can
 ## be derived more directly via the theory of Cauchy matrices.
-## See J. W. Demmel, @cite{Applied Numerical Linear Algebra}, p. 92.
+## See @nospell{J. W. Demmel}, @cite{Applied Numerical Linear Algebra}, p. 92.
 ##
 ## Compare this with the numerical calculation of @code{inverse (hilb (n))},
 ## which suffers from the ill-conditioning of the Hilbert matrix, and the

--- a/scripts/statistics/base/quantile.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/statistics/base/quantile.m	Thu Aug 21 15:57:18 2014 -0700
@@ -73,17 +73,17 @@
 ## @var{x} is normally distributed.
 ## @end enumerate
 ##
-## Hyndman and Fan (1996) recommend method 8.  Maxima, S, and R
+## @nospell{Hyndman and Fan} (1996) recommend method 8.  Maxima, S, and R
 ## (versions prior to 2.0.0) use 7 as their default.  Minitab and SPSS
 ## use method 6.  @sc{matlab} uses method 5.
 ##
 ## References:
 ##
 ## @itemize @bullet
-## @item Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New
-## S Language.  Wadsworth & Brooks/Cole.
+## @item @nospell{Becker, R. A., Chambers, J. M. and Wilks, A. R.} (1988)
+## The New S Language.  Wadsworth & Brooks/Cole.
 ##
-## @item Hyndman, R. J. and Fan, Y. (1996) Sample quantiles in
+## @item @nospell{Hyndman, R. J. and Fan, Y.} (1996) Sample quantiles in
 ## statistical packages, American Statistician, 50, 361--365.
 ##
 ## @item R: A Language and Environment for Statistical Computing;

--- a/scripts/statistics/tests/kruskal_wallis_test.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/statistics/tests/kruskal_wallis_test.m	Thu Aug 21 15:57:18 2014 -0700
@@ -18,7 +18,7 @@
 
 ## -*- texinfo -*-
 ## @deftypefn {Function File} {[@var{pval}, @var{k}, @var{df}] =} kruskal_wallis_test (@var{x1}, @dots{})
-## Perform a Kruskal-Wallis one-factor analysis of variance.
+## Perform a @nospell{Kruskal-Wallis} one-factor analysis of variance.
 ##
 ## Suppose a variable is observed for @var{k} > 1 different groups, and
 ## let @var{x1}, @dots{}, @var{xk} be the corresponding data vectors.
@@ -36,7 +36,7 @@
 ## where @var{sum_ties} is the sum of @var{t}^2 - @var{t} over each group
 ## of ties where @var{t} is the number of ties in the group and @var{n}
 ## is the total number of values in the input data.  For more info on
-## this adjustment see William H. Kruskal and W. Allen Wallis,
+## this adjustment see @nospell{William H. Kruskal and W. Allen Wallis},
 ## @cite{Use of Ranks in One-Criterion Variance Analysis}, 
 ## Journal of the American Statistical Association, Vol. 47,
 ## No. 260 (Dec 1952).

--- a/scripts/statistics/tests/manova.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/statistics/tests/manova.m	Thu Aug 21 15:57:18 2014 -0700
@@ -28,7 +28,7 @@
 ## and columns are variables.  The vector @var{g} specifies the
 ## corresponding group labels (e.g., numbers from 1 to @var{k}).
 ##
-## The LR test statistic (Wilks' Lambda) and approximate p-values are
+## The LR test statistic (@nospell{Wilks' Lambda}) and approximate p-values are
 ## computed and displayed.
 ## @end deftypefn
 

--- a/scripts/statistics/tests/mcnemar_test.m	Thu Aug 21 18:49:47 2014 +0100
+++ b/scripts/statistics/tests/mcnemar_test.m	Thu Aug 21 15:57:18 2014 -0700
@@ -19,8 +19,8 @@
 ## -*- texinfo -*-
 ## @deftypefn {Function File} {[@var{pval}, @var{chisq}, @var{df}] =} mcnemar_test (@var{x})
 ## For a square contingency table @var{x} of data cross-classified on
-## the row and column variables, McNemar's test can be used for testing
-## the null hypothesis of symmetry of the classification probabilities.
+## the row and column variables, @nospell{McNemar's} test can be used for
+## testing the null hypothesis of symmetry of the classification probabilities.
 ##
 ## Under the null, @var{chisq} is approximately distributed as chisquare
 ## with @var{df} degrees of freedom.