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Modernize docstrings: drop @multitable spacer columns, use * in @math dimensions.
 * inst/mvksdensity.m: Replace the bare 'x' with '*' in the @math matrix dimension expressions (NxD, MxD, Mx1, 1xD). * inst/dist_obj/StableDistribution.m: Likewise for 4x1, 4x4, and 2x4. * inst/dist_obj/BinomialDistribution.m: Drop the empty middle spacer column from the plot Name-Value @multitable (@columnfractions 0.18 0.02 0.8 -> 0.18 0.8), removing the extra @tab from the header and item rows. * inst/dist_obj/MultinomialDistribution.m: Likewise. * inst/dist_obj/BetaDistribution.m: Likewise. * inst/doc-cache: Regenerate the mvksdensity entry.
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‎inst/dist_obj/BetaDistribution.m‎

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@@ -521,10 +521,10 @@ function disp (this)
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## @code{plot (@var{pd}, @var{Name}, @var{Value})} specifies additional
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## options with the @qcode{Name-Value} pair arguments listed below.
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##
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## @multitable @columnfractions 0.18 0.02 0.8
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## @headitem @tab @var{Name} @tab @var{Value}
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## @multitable @columnfractions 0.18 0.8
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## @headitem @var{Name} @tab @var{Value}
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##
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## @item @qcode{'PlotType'} @tab @tab A character vector specifying the plot
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## @item @qcode{'PlotType'} @tab A character vector specifying the plot
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## type. @qcode{'pdf'} plots the probability density function (PDF). When
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## @var{pd} is fit to data, the PDF is superimposed on a histogram of the
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## data. @qcode{'cdf'} plots the cumulative density function (CDF). When
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## and a CDF of the fitted probability distribution. This option is
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## available only when @var{pd} is fitted to data.
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##
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## @item @qcode{'Discrete'} @tab @tab A logical scalar to specify whether to
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## @item @qcode{'Discrete'} @tab A logical scalar to specify whether to
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## plot the PDF or CDF of a discrete distribution object as a line plot or a
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## stem plot, by specifying @qcode{false} or @qcode{true}, respectively. By
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## default, it is @qcode{true} for discrete distributions and @qcode{false}
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## for continuous distributions. When @var{pd} is a continuous distribution
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## object, option is ignored.
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##
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## @item @qcode{'Parent'} @tab @tab An axes graphics object for plot. If
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## @item @qcode{'Parent'} @tab An axes graphics object for plot. If
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## not specified, the @code{plot} function plots into the current axes or
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## creates a new axes object if one does not exist.
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## @end multitable

‎inst/dist_obj/BinomialDistribution.m‎

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@@ -529,10 +529,10 @@ function disp (this)
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## @code{plot (@var{pd}, @var{Name}, @var{Value})} specifies additional
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## options with the @qcode{Name-Value} pair arguments listed below.
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##
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## @multitable @columnfractions 0.18 0.02 0.8
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## @headitem @tab @var{Name} @tab @var{Value}
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## @multitable @columnfractions 0.18 0.8
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## @headitem @var{Name} @tab @var{Value}
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##
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## @item @qcode{'PlotType'} @tab @tab A character vector specifying the plot
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## @item @qcode{'PlotType'} @tab A character vector specifying the plot
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## type. @qcode{'pdf'} plots the probability density function (PDF). When
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## @var{pd} is fit to data, the PDF is superimposed on a histogram of the
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## data. @qcode{'cdf'} plots the cumulative density function (CDF). When
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## and a CDF of the fitted probability distribution. This option is
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## available only when @var{pd} is fitted to data.
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##
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## @item @qcode{'Discrete'} @tab @tab A logical scalar to specify whether to
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## @item @qcode{'Discrete'} @tab A logical scalar to specify whether to
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## plot the PDF or CDF of a discrete distribution object as a line plot or a
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## stem plot, by specifying @qcode{false} or @qcode{true}, respectively. By
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## default, it is @qcode{true} for discrete distributions and @qcode{false}
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## for continuous distributions. When @var{pd} is a continuous distribution
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## object, option is ignored.
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##
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## @item @qcode{'Parent'} @tab @tab An axes graphics object for plot. If
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## @item @qcode{'Parent'} @tab An axes graphics object for plot. If
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## not specified, the @code{plot} function plots into the current axes or
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## creates a new axes object if one does not exist.
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## @end multitable

‎inst/dist_obj/MultinomialDistribution.m‎

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@@ -405,10 +405,10 @@ function disp (this)
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## @code{plot (@var{pd}, @var{Name}, @var{Value})} specifies additional
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## options with the @qcode{Name-Value} pair arguments listed below.
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##
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## @multitable @columnfractions 0.18 0.02 0.8
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## @headitem @tab @var{Name} @tab @var{Value}
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## @multitable @columnfractions 0.18 0.8
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## @headitem @var{Name} @tab @var{Value}
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##
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## @item @qcode{'PlotType'} @tab @tab A character vector specifying the plot
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## @item @qcode{'PlotType'} @tab A character vector specifying the plot
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## type. @qcode{'pdf'} plots the probability density function (PDF). When
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## @var{pd} is fit to data, the PDF is superimposed on a histogram of the
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## data. @qcode{'cdf'} plots the cumulative density function (CDF). When
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## and a CDF of the fitted probability distribution. This option is
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## available only when @var{pd} is fitted to data.
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##
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## @item @qcode{'Discrete'} @tab @tab A logical scalar to specify whether to
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## @item @qcode{'Discrete'} @tab A logical scalar to specify whether to
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## plot the PDF or CDF of a discrete distribution object as a line plot or a
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## stem plot, by specifying @qcode{false} or @qcode{true}, respectively. By
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## default, it is @qcode{true} for discrete distributions and @qcode{false}
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## for continuous distributions. When @var{pd} is a continuous distribution
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## object, option is ignored.
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##
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## @item @qcode{'Parent'} @tab @tab An axes graphics object for plot. If
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## @item @qcode{'Parent'} @tab An axes graphics object for plot. If
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## not specified, the @code{plot} function plots into the current axes or
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## creates a new axes object if one does not exist.
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## @end multitable

‎inst/dist_obj/StableDistribution.m‎

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##
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## Names of parameters
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##
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## A @math{4x1} cell array of character vectors with each element containing
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## A @math{4*1} cell array of character vectors with each element containing
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## the name of a distribution parameter. This property is read-only.
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##
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## @end deftp
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##
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## Description of parameters
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##
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## A @math{4x1} cell array of character vectors with each element containing
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## A @math{4*1} cell array of character vectors with each element containing
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## a short description of a distribution parameter. This property is
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## read-only.
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##
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##
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## Distribution parameter values
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##
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## A @math{4x1} numeric vector containing the values of the distribution
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## A @math{4*1} numeric vector containing the values of the distribution
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## parameters, matching the order in @qcode{ParameterNames}. This property
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## is read-only; use dot name assignment on the @qcode{alpha}, @qcode{beta},
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## @qcode{gam}, and @qcode{delta} properties.
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##
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## Covariance matrix of the parameter estimates
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##
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## A @math{4x4} numeric matrix containing the variance-covariance of the
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## A @math{4*4} numeric matrix containing the variance-covariance of the
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## distribution parameters. This property is read-only.
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##
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## @end deftp
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##
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## Confidence intervals for the parameter estimates
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##
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## A @math{2x4} numeric matrix containing the lower and upper boundaries of
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## A @math{2*4} numeric matrix containing the lower and upper boundaries of
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## the confidence interval for each parameter, when the distribution has been
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## fitted to data. This property is read-only.
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##
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##
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## Flags for fixed parameters
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##
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## A @math{4x1} logical vector specifying which parameters are held fixed
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## A @math{4*1} logical vector specifying which parameters are held fixed
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## rather than estimated. This property is read-only.
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##
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## @end deftp

‎inst/doc-cache‎

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@@ -9619,9 +9619,9 @@ mvksdensity
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Multivariate kernel smoothing density estimate.
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‘F = mvksdensity (X, PTS)’ computes a probability density estimate of the
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sample in the NxD matrix X, evaluated at the points in the MxD matrix PTS.
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sample in the N*D matrix X, evaluated at the points in the M*D matrix PTS.
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Each row of X is a single D-dimensional observation, and each row of PTS is
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a point at which to evaluate the estimate. The result F is an Mx1 vector,
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a point at which to evaluate the estimate. The result F is an M*1 vector,
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with one density value per row of PTS.
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The density estimate uses a product kernel: the multivariate kernel is the
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----------------------------------------------------------------------------------
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'Bandwidth' The kernel bandwidth, either a positive scalar applied to every
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dimension or a 1xD vector of positive values, one per dimension.
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dimension or a 1*D vector of positive values, one per dimension.
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The default is a diagonal normal-reference (Silverman) rule
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computed from X.
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‎inst/mvksdensity.m‎

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## Multivariate kernel smoothing density estimate.
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##
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## @code{@var{f} = mvksdensity (@var{x}, @var{pts})} computes a probability
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## density estimate of the sample in the @math{NxD} matrix @var{x}, evaluated at
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## the points in the @math{MxD} matrix @var{pts}. Each row of @var{x} is a
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## density estimate of the sample in the @math{N*D} matrix @var{x}, evaluated at
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## the points in the @math{M*D} matrix @var{pts}. Each row of @var{x} is a
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## single @math{D}-dimensional observation, and each row of @var{pts} is a point
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## at which to evaluate the estimate. The result @var{f} is an @math{Mx1}
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## at which to evaluate the estimate. The result @var{f} is an @math{M*1}
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## vector, with one density value per row of @var{pts}.
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##
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## The density estimate uses a product kernel: the multivariate kernel is the
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## @headitem @var{Name} @tab @var{Value}
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##
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## @item @qcode{'Bandwidth'} @tab The kernel bandwidth, either a positive scalar
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## applied to every dimension or a @math{1xD} vector of positive values, one per
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## applied to every dimension or a @math{1*D} vector of positive values, one per
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## dimension. The default is a diagonal normal-reference (Silverman) rule
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## computed from @var{x}.
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##

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