--- a/src/DLD-FUNCTIONS/cellfun.cc	Mon Feb 13 07:42:56 2012 -0800
+++ b/src/DLD-FUNCTIONS/cellfun.cc	Mon Feb 13 07:45:41 2012 -0800
@@ -257,8 +257,8 @@
 @deftypefnx {Loadable Function} {} cellfun (@var{func}, @var{C})\n\
 @deftypefnx {Loadable Function} {} cellfun (@var{func}, @var{C}, @var{D})\n\
 @deftypefnx {Loadable Function} {[@var{a}, @dots{}] =} cellfun (@dots{})\n\
-@deftypefnx {Loadable Function} {} cellfun (@dots{}, 'ErrorHandler', @var{errfunc})\n\
-@deftypefnx {Loadable Function} {} cellfun (@dots{}, 'UniformOutput', @var{val})\n\
+@deftypefnx {Loadable Function} {} cellfun (@dots{}, \"ErrorHandler\", @var{errfunc})\n\
+@deftypefnx {Loadable Function} {} cellfun (@dots{}, \"UniformOutput\", @var{val})\n\
 \n\
 Evaluate the function named @var{name} on the elements of the cell array\n\
 @var{C}.  Elements in @var{C} are passed on to the named function\n\
@@ -332,7 +332,7 @@
 \n\
 If the parameter \"UniformOutput\" is set to true (the default), then the\n\
 function must return scalars which will be concatenated into the return\n\
-array(s).  If 'UniformOutput' is false, the outputs are concatenated into a\n\
+array(s).  If \"UniformOutput\" is false, the outputs are concatenated into a\n\
 cell array (or cell arrays).  For example:\n\
 \n\
 @example\n\
@@ -343,7 +343,7 @@
 @end group\n\
 @end example\n\
 \n\
-Given the parameter 'ErrorHandler', then @var{errfunc} defines a function to\n\
+Given the parameter \"ErrorHandler\", then @var{errfunc} defines a function to\n\
 call in case @var{func} generates an error.  The form of the function is\n\
 \n\
 @example\n\

--- a/src/DLD-FUNCTIONS/chol.cc	Mon Feb 13 07:42:56 2012 -0800
+++ b/src/DLD-FUNCTIONS/chol.cc	Mon Feb 13 07:45:41 2012 -0800
@@ -65,9 +65,9 @@
 @deftypefn  {Loadable Function} {@var{R} =} chol (@var{A})\n\
 @deftypefnx {Loadable Function} {[@var{R}, @var{p}] =} chol (@var{A})\n\
 @deftypefnx {Loadable Function} {[@var{R}, @var{p}, @var{Q}] =} chol (@var{S})\n\
-@deftypefnx {Loadable Function} {[@var{R}, @var{p}, @var{Q}] =} chol (@var{S}, 'vector')\n\
-@deftypefnx {Loadable Function} {[@var{L}, @dots{}] =} chol (@dots{}, 'lower')\n\
-@deftypefnx {Loadable Function} {[@var{L}, @dots{}] =} chol (@dots{}, 'upper')\n\
+@deftypefnx {Loadable Function} {[@var{R}, @var{p}, @var{Q}] =} chol (@var{S}, \"vector\")\n\
+@deftypefnx {Loadable Function} {[@var{L}, @dots{}] =} chol (@dots{}, \"lower\")\n\
+@deftypefnx {Loadable Function} {[@var{L}, @dots{}] =} chol (@dots{}, \"upper\")\n\
 @cindex Cholesky factorization\n\
 Compute the Cholesky@tie{}factor, @var{R}, of the symmetric positive definite\n\
 matrix @var{A}, where\n\
@@ -103,7 +103,7 @@
 @end ifnottex\n\
 \n\
 The sparsity preserving permutation is generally returned as a matrix.\n\
-However, given the flag 'vector', @var{Q} will be returned as a vector\n\
+However, given the flag \"vector\", @var{Q} will be returned as a vector\n\
 such that\n\
 @tex\n\
 $ R^T R = A (Q, Q)$.\n\
@@ -116,7 +116,7 @@
 \n\
 @end ifnottex\n\
 \n\
-Called with either a sparse or full matrix and using the 'lower' flag,\n\
+Called with either a sparse or full matrix and using the \"lower\" flag,\n\
 @code{chol} returns the lower triangular factorization such that\n\
 @tex\n\
 $ L L^T = A $.\n\
@@ -129,7 +129,7 @@
 \n\
 @end ifnottex\n\
 \n\
-For full matrices, if the 'lower' flag is set only the lower triangular part\n\
+For full matrices, if the \"lower\" flag is set only the lower triangular part\n\
 of the matrix is used for the factorization, otherwise the upper triangular\n\
 part is used.\n\
 \n\

--- a/src/DLD-FUNCTIONS/colamd.cc	Mon Feb 13 07:42:56 2012 -0800
+++ b/src/DLD-FUNCTIONS/colamd.cc	Mon Feb 13 07:45:41 2012 -0800
@@ -651,7 +651,7 @@
 is assumed to be symmetric and the symmetric elimination tree is\n\
 returned.  The argument @var{typ} controls whether a symmetric or\n\
 column elimination tree is returned.  Valid values of @var{typ} are\n\
-'sym' or 'col', for symmetric or column elimination tree respectively\n\
+\"sym\" or \"col\", for symmetric or column elimination tree respectively\n\
 \n\
 Called with a second argument, @code{etree} also returns the postorder\n\
 permutations on the tree.\n\

--- a/src/DLD-FUNCTIONS/dlmread.cc	Mon Feb 13 07:42:56 2012 -0800
+++ b/src/DLD-FUNCTIONS/dlmread.cc	Mon Feb 13 07:45:41 2012 -0800
@@ -173,7 +173,7 @@
 The @var{range} parameter may be a 4-element vector containing the upper\n\
 left and lower right corner @code{[@var{R0},@var{C0},@var{R1},@var{C1}]}\n\
 where the lowest index value is zero.  Alternatively, a spreadsheet style\n\
-range such as 'A2..Q15' or 'T1:AA5' can be used.  The lowest alphabetical\n\
+range such as \"A2..Q15\" or \"T1:AA5\" can be used.  The lowest alphabetical\n\
 index 'A' refers to the first column.  The lowest row index is 1.\n\
 \n\
 @var{file} should be a file name or file id given by @code{fopen}.  In the\n\

--- a/src/DLD-FUNCTIONS/eigs.cc	Mon Feb 13 07:42:56 2012 -0800
+++ b/src/DLD-FUNCTIONS/eigs.cc	Mon Feb 13 07:45:41 2012 -0800
@@ -184,32 +184,32 @@
 @var{sigma} is a string, it must have one of the following values.\n\
 \n\
 @table @asis\n\
-@item 'lm'\n\
+@item \"lm\"\n\
 Largest Magnitude (default).\n\
 \n\
-@item 'sm'\n\
+@item \"sm\"\n\
 Smallest Magnitude.\n\
 \n\
-@item 'la'\n\
+@item \"la\"\n\
 Largest Algebraic (valid only for real symmetric problems).\n\
 \n\
-@item 'sa'\n\
+@item \"sa\"\n\
 Smallest Algebraic (valid only for real symmetric problems).\n\
 \n\
-@item 'be'\n\
+@item \"be\"\n\
 Both Ends, with one more from the high-end if @var{k} is odd (valid only for\n\
 real symmetric problems).\n\
 \n\
-@item 'lr'\n\
+@item \"lr\"\n\
 Largest Real part (valid only for complex or unsymmetric problems).\n\
 \n\
-@item 'sr'\n\
+@item \"sr\"\n\
 Smallest Real part (valid only for complex or unsymmetric problems).\n\
 \n\
-@item 'li'\n\
+@item \"li\"\n\
 Largest Imaginary part (valid only for complex or unsymmetric problems).\n\
 \n\
-@item 'si'\n\
+@item \"si\"\n\
 Smallest Imaginary part (valid only for complex or unsymmetric problems).\n\
 @end table\n\
 \n\
@@ -270,10 +270,10 @@
 \n\
 @table @code\n\
 @item A * x\n\
-if @var{sigma} is not given or is a string other than 'sm'.\n\
+if @var{sigma} is not given or is a string other than \"sm\".\n\
 \n\
 @item A \\ x\n\
-if @var{sigma} is 0 or 'sm'.\n\
+if @var{sigma} is 0 or \"sm\".\n\
 \n\
 @item (A - sigma * I) \\ x\n\
 for the standard eigenvalue problem, where @code{I} is the identity matrix of\n\

--- a/src/DLD-FUNCTIONS/fftw.cc	Mon Feb 13 07:42:56 2012 -0800
+++ b/src/DLD-FUNCTIONS/fftw.cc	Mon Feb 13 07:45:41 2012 -0800
@@ -34,10 +34,10 @@
 
 DEFUN_DLD (fftw, args, ,
   "-*- texinfo -*-\n\
-@deftypefn  {Loadable Function} {@var{method} =} fftw ('planner')\n\
-@deftypefnx {Loadable Function} {} fftw ('planner', @var{method})\n\
-@deftypefnx {Loadable Function} {@var{wisdom} =} fftw ('dwisdom')\n\
-@deftypefnx {Loadable Function} {} fftw ('dwisdom', @var{wisdom})\n\
+@deftypefn  {Loadable Function} {@var{method} =} fftw (\"planner\")\n\
+@deftypefnx {Loadable Function} {} fftw (\"planner\", @var{method})\n\
+@deftypefnx {Loadable Function} {@var{wisdom} =} fftw (\"dwisdom\")\n\
+@deftypefnx {Loadable Function} {} fftw (\"dwisdom\", @var{wisdom})\n\
 \n\
 Manage @sc{fftw} wisdom data.  Wisdom data can be used to significantly\n\
 accelerate the calculation of the FFTs, but implies an initial cost\n\
@@ -68,31 +68,31 @@
 wisdom can be treated:\n\
 \n\
 @table @asis\n\
-@item 'estimate'\n\
+@item \"estimate\"\n\
 Specifies that no run-time measurement of the optimal means of\n\
 calculating a particular is performed, and a simple heuristic is used\n\
 to pick a (probably sub-optimal) plan.  The advantage of this method is\n\
 that there is little or no overhead in the generation of the plan, which\n\
 is appropriate for a Fourier transform that will be calculated once.\n\
 \n\
-@item 'measure'\n\
+@item \"measure\"\n\
 In this case a range of algorithms to perform the transform is considered\n\
 and the best is selected based on their execution time.\n\
 \n\
-@item 'patient'\n\
-Similar to 'measure', but a wider range of algorithms is considered.\n\
+@item \"patient\"\n\
+Similar to \"measure\", but a wider range of algorithms is considered.\n\
 \n\
-@item 'exhaustive'\n\
-Like 'measure', but all possible algorithms that may be used to\n\
+@item \"exhaustive\"\n\
+Like \"measure\", but all possible algorithms that may be used to\n\
 treat the transform are considered.\n\
 \n\
-@item 'hybrid'\n\
+@item \"hybrid\"\n\
 As run-time measurement of the algorithm can be expensive, this is a\n\
-compromise where 'measure' is used for transforms up to the size of 8192\n\
-and beyond that the 'estimate' method is used.\n\
+compromise where \"measure\" is used for transforms up to the size of 8192\n\
+and beyond that the \"estimate\" method is used.\n\
 @end table\n\
 \n\
-The default method is 'estimate'.  The current method can\n\
+The default method is \"estimate\".  The current method can\n\
 be queried with\n\
 \n\
 @example\n\

--- a/src/DLD-FUNCTIONS/lu.cc	Mon Feb 13 07:42:56 2012 -0800
+++ b/src/DLD-FUNCTIONS/lu.cc	Mon Feb 13 07:45:41 2012 -0800
@@ -69,7 +69,7 @@
 @deftypefnx {Loadable Function} {[@var{L}, @var{U}, @var{P}, @var{Q}, @var{R}] =} lu (@var{S})\n\
 @deftypefnx {Loadable Function} {[@dots{}] =} lu (@var{S}, @var{thres})\n\
 @deftypefnx {Loadable Function} {@var{y} =} lu (@dots{})\n\
-@deftypefnx {Loadable Function} {[@dots{}] =} lu (@dots{}, 'vector')\n\
+@deftypefnx {Loadable Function} {[@dots{}] =} lu (@dots{}, \"vector\")\n\
 @cindex LU decomposition\n\
 Compute the LU@tie{}decomposition of @var{A}.  If @var{A} is full\n\
 subroutines from\n\
@@ -125,7 +125,7 @@
 pivoting strategy and the second for the symmetric strategy.  By default,\n\
 the values defined by @code{spparms} are used ([0.1, 0.001]).\n\
 \n\
-Given the string argument 'vector', @code{lu} returns the values of @var{P}\n\
+Given the string argument \"vector\", @code{lu} returns the values of @var{P}\n\
 and @var{Q} as vector values, such that for full matrix, @code{@var{A}\n\
 (@var{P},:) = @var{L} * @var{U}}, and @code{@var{R}(@var{P},:) * @var{A}\n\
 (:, @var{Q}) = @var{L} * @var{U}}.\n\

--- a/src/DLD-FUNCTIONS/luinc.cc	Mon Feb 13 07:42:56 2012 -0800
+++ b/src/DLD-FUNCTIONS/luinc.cc	Mon Feb 13 07:45:41 2012 -0800
@@ -91,7 +91,7 @@
 All other fields in @var{opts} are ignored.  The outputs from @code{luinc}\n\
 are the same as for @code{lu}.\n\
 \n\
-Given the string argument 'vector', @code{luinc} returns the values of\n\
+Given the string argument \"vector\", @code{luinc} returns the values of\n\
 @var{p} @var{q} as vector values.\n\
 @seealso{sparse, lu}\n\
 @end deftypefn")

--- a/src/DLD-FUNCTIONS/matrix_type.cc	Mon Feb 13 07:42:56 2012 -0800
+++ b/src/DLD-FUNCTIONS/matrix_type.cc	Mon Feb 13 07:45:41 2012 -0800
@@ -39,59 +39,59 @@
 DEFUN_DLD (matrix_type, args, ,
   "-*- texinfo -*-\n\
 @deftypefn  {Loadable Function} {@var{type} =} matrix_type (@var{A})\n\
-@deftypefnx {Loadable Function} {@var{type} =} matrix_type (@var{A}, 'nocompute')\n\
+@deftypefnx {Loadable Function} {@var{type} =} matrix_type (@var{A}, \"nocompute\")\n\
 @deftypefnx {Loadable Function} {@var{A} =} matrix_type (@var{A}, @var{type})\n\
-@deftypefnx {Loadable Function} {@var{A} =} matrix_type (@var{A}, 'upper', @var{perm})\n\
-@deftypefnx {Loadable Function} {@var{A} =} matrix_type (@var{A}, 'lower', @var{perm})\n\
-@deftypefnx {Loadable Function} {@var{A} =} matrix_type (@var{A}, 'banded', @var{nl}, @var{nu})\n\
+@deftypefnx {Loadable Function} {@var{A} =} matrix_type (@var{A}, \"upper\", @var{perm})\n\
+@deftypefnx {Loadable Function} {@var{A} =} matrix_type (@var{A}, \"lower\", @var{perm})\n\
+@deftypefnx {Loadable Function} {@var{A} =} matrix_type (@var{A}, \"banded\", @var{nl}, @var{nu})\n\
 Identify the matrix type or mark a matrix as a particular type.  This allows\n\
 more rapid solutions of linear equations involving @var{A} to be performed.\n\
 Called with a single argument, @code{matrix_type} returns the type of the\n\
 matrix and caches it for future use.  Called with more than one argument,\n\
 @code{matrix_type} allows the type of the matrix to be defined.\n\
 \n\
-If the option 'nocompute' is given, the function will not attempt to guess\n\
+If the option \"nocompute\" is given, the function will not attempt to guess\n\
 the type if it is still unknown.  This is useful for debugging purposes.\n\
 \n\
 The possible matrix types depend on whether the matrix is full or sparse, and\n\
 can be one of the following\n\
 \n\
 @table @asis\n\
-@item 'unknown'\n\
+@item \"unknown\"\n\
 Remove any previously cached matrix type, and mark type as unknown.\n\
 \n\
-@item 'full'\n\
+@item \"full\"\n\
 Mark the matrix as full.\n\
 \n\
-@item 'positive definite'\n\
+@item \"positive definite\"\n\
 Probable full positive definite matrix.\n\
 \n\
-@item 'diagonal'\n\
+@item \"diagonal\"\n\
 Diagonal matrix.  (Sparse matrices only)\n\
 \n\
-@item 'permuted diagonal'\n\
+@item \"permuted diagonal\"\n\
 Permuted Diagonal matrix.  The permutation does not need to be specifically\n\
 indicated, as the structure of the matrix explicitly gives this.  (Sparse\n\
 matrices only)\n\
 \n\
-@item 'upper'\n\
+@item \"upper\"\n\
 Upper triangular.  If the optional third argument @var{perm} is given, the\n\
 matrix is assumed to be a permuted upper triangular with the permutations\n\
 defined by the vector @var{perm}.\n\
 \n\
-@item 'lower'\n\
+@item \"lower\"\n\
 Lower triangular.  If the optional third argument @var{perm} is given, the\n\
 matrix is assumed to be a permuted lower triangular with the permutations\n\
 defined by the vector @var{perm}.\n\
 \n\
-@item 'banded'\n\
-@itemx 'banded positive definite'\n\
+@item \"banded\"\n\
+@itemx \"banded positive definite\"\n\
 Banded matrix with the band size of @var{nl} below the diagonal and @var{nu}\n\
 above it.  If @var{nl} and @var{nu} are 1, then the matrix is tridiagonal and\n\
 treated with specialized code.  In addition the matrix can be marked as\n\
 probably a positive definite.  (Sparse matrices only)\n\
 \n\
-@item 'singular'\n\
+@item \"singular\"\n\
 The matrix is assumed to be singular and will be treated with a minimum norm\n\
 solution.\n\
 \n\

--- a/src/DLD-FUNCTIONS/spparms.cc	Mon Feb 13 07:42:56 2012 -0800
+++ b/src/DLD-FUNCTIONS/spparms.cc	Mon Feb 13 07:45:41 2012 -0800
@@ -40,8 +40,8 @@
 @deftypefnx {Loadable Function} {[@var{keys}, @var{vals}] =} spparms ()\n\
 @deftypefnx {Loadable Function} {@var{val} =} spparms (@var{key})\n\
 @deftypefnx {Loadable Function} { } spparms (@var{vals})\n\
-@deftypefnx {Loadable Function} { } spparms ('defaults')\n\
-@deftypefnx {Loadable Function} { } spparms ('tight')\n\
+@deftypefnx {Loadable Function} { } spparms (\"defaults\")\n\
+@deftypefnx {Loadable Function} { } spparms (\"tight\")\n\
 @deftypefnx {Loadable Function} { } spparms (@var{key}, @var{val})\n\
 Query or set the parameters used by the sparse solvers and factorization\n\
 functions.  The first four calls above get information about the current\n\
@@ -97,7 +97,7 @@
 The value of individual keys can be set with\n\
 @code{spparms (@var{key}, @var{val})}.\n\
 The default values can be restored with the special keyword\n\
-'defaults'.  The special keyword 'tight' can be used to set the mmd solvers\n\
+\"defaults\".  The special keyword \"tight\" can be used to set the mmd solvers\n\
 to attempt a sparser solution at the potential cost of longer running\n\
 time.\n\
 @end deftypefn")

--- a/src/DLD-FUNCTIONS/symrcm.cc	Mon Feb 13 07:42:56 2012 -0800
+++ b/src/DLD-FUNCTIONS/symrcm.cc	Mon Feb 13 07:45:41 2012 -0800
@@ -422,7 +422,7 @@
 @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\
-or Cholesky@tie{}factorization of matrices that come from 'long, skinny'\n\
+or Cholesky@tie{}factorization of matrices that come from ``long, skinny''\n\
 problems.  It works for both symmetric and asymmetric @var{S}.\n\
 \n\
 The algorithm represents a heuristic approach to the NP-complete\n\

--- a/src/data.cc	Mon Feb 13 07:42:56 2012 -0800
+++ b/src/data.cc	Mon Feb 13 07:45:41 2012 -0800
@@ -1093,14 +1093,14 @@
   "-*- texinfo -*-\n\
 @deftypefn  {Built-in Function} {} cumsum (@var{x})\n\
 @deftypefnx {Built-in Function} {} cumsum (@var{x}, @var{dim})\n\
-@deftypefnx {Built-in Function} {} cumsum (@dots{}, 'native')\n\
-@deftypefnx {Built-in Function} {} cumsum (@dots{}, 'double')\n\
-@deftypefnx {Built-in Function} {} cumsum (@dots{}, 'extra')\n\
+@deftypefnx {Built-in Function} {} cumsum (@dots{}, \"native\")\n\
+@deftypefnx {Built-in Function} {} cumsum (@dots{}, \"double\")\n\
+@deftypefnx {Built-in Function} {} cumsum (@dots{}, \"extra\")\n\
 Cumulative sum of elements along dimension @var{dim}.  If @var{dim}\n\
 is omitted, it defaults to the first non-singleton dimension.\n\
 \n\
-See @code{sum} for an explanation of the optional parameters 'native',\n\
-'double', and 'extra'.\n\
+See @code{sum} for an explanation of the optional parameters \"native\",\n\
+\"double\", and \"extra\".\n\
 @seealso{sum, cumprod}\n\
 @end deftypefn")
 {
@@ -5869,7 +5869,7 @@
 If the optional argument @var{dim} is given, then the matrix is sorted\n\
 along the dimension defined by @var{dim}.  The optional argument @code{mode}\n\
 defines the order in which the values will be sorted.  Valid values of\n\
-@code{mode} are `ascend' or `descend'.\n\
+@code{mode} are \"ascend\" or \"descend\".\n\
 \n\
 The @code{sort} function may also be used to produce a matrix\n\
 containing the original row indices of the elements in the sorted\n\

--- a/src/dirfns.cc	Mon Feb 13 07:42:56 2012 -0800
+++ b/src/dirfns.cc	Mon Feb 13 07:45:41 2012 -0800
@@ -687,10 +687,10 @@
 DEFUN (filesep, args, ,
   "-*- texinfo -*-\n\
 @deftypefn  {Built-in Function} {} filesep ()\n\
-@deftypefnx {Built-in Function} {} filesep ('all')\n\
+@deftypefnx {Built-in Function} {} filesep (\"all\")\n\
 Return the system-dependent character used to separate directory names.\n\
 \n\
-If 'all' is given, the function returns all valid file separators in\n\
+If \"all\" is given, the function returns all valid file separators in\n\
 the form of a string.  The list of file separators is system-dependent.\n\
 It is @samp{/} (forward slash) under UNIX or @w{Mac OS X}, @samp{/} and\n\
 @samp{\\} (forward and backward slashes) under Windows.\n\

--- a/src/error.cc	Mon Feb 13 07:42:56 2012 -0800
+++ b/src/error.cc	Mon Feb 13 07:45:41 2012 -0800
@@ -1487,7 +1487,7 @@
   "-*- texinfo -*-\n\
 @deftypefn  {Built-in Function} {@var{lasterr} =} lasterror ()\n\
 @deftypefnx {Built-in Function} {} lasterror (@var{err})\n\
-@deftypefnx {Built-in Function} {} lasterror ('reset')\n\
+@deftypefnx {Built-in Function} {} lasterror (\"reset\")\n\
 Query or set the last error message structure.  When called without\n\
 arguments, return a structure containing the last error message and other\n\
 information related to this error.  The elements of the structure are:\n\
@@ -1523,7 +1523,7 @@
 as input.  Any fields of @var{err} that match those above are set while any\n\
 unspecified fields are initialized with default values.\n\
 \n\
-If @code{lasterror} is called with the argument 'reset', all fields are\n\
+If @code{lasterror} is called with the argument \"reset\", all fields are\n\
 set to their default values.\n\
 @seealso{lasterr}\n\
 @end deftypefn")