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Diff for /OpenXM/src/R/r-client/Ropenxm/man/oxm.markov.Rd between version 1.1 and 1.2

version 1.1, 2013/02/01 07:14:09 version 1.2, 2013/02/02 05:16:44
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   % $OpenXM$
 \name{oxm.markov}  \name{oxm.markov}
 \alias{oxm.markov}  \alias{oxm.markov}
 %- Also NEED an '\alias' for EACH other topic documented here.  %- Also NEED an '\alias' for EACH other topic documented here.
 \title{  \title{
   It obtains the Markov basis for a given set of points by an OpenXM server.    The function oxm.markov obtains the Markov basis for a given set of points by 4ti2 through an OpenXM server.
 }  }
 \description{  \description{
 %%  ~~ A concise (1-5 lines) description of what the function does. ~~    The function oxm.markov obtains the Markov basis for a given set of points by 4ti2 through an OpenXM server.
     It is provided also for a sample implementation to call OpenXM servers from R.
 }  }
 \usage{  \usage{
 oxm.markov(mat)  oxm.markov(mat,url="http://polymake.math.kobe-u.ac.jp/cgi-bin/cgi-asir-r-markov.sh")
 }  }
 %- maybe also 'usage' for other objects documented here.  %- maybe also 'usage' for other objects documented here.
 \arguments{  \arguments{
   \item{mat}{    \item{mat}{
 %%     ~~Describe \code{mat} here~~       A matrix which represents a set of integer points.
        Each column of the matrix is each point of the set.
     }
     \item{url}{
       This argument specifies the URL of an OpenXM server.
     The default is an anonymous server in public set by the openxm.org.
     Note that all inputs are recorded in the server
     and the privacy policy of the public server declares
     that the record is used only for debugging and for security tasks.
     You can specify your own server.
     }
 }  }
 }  
 \details{  \details{
 %%  ~~ If necessary, more details than the description above ~~    A general algorithm to obtain the Markov basis for a set of points
     was given in
     "P.Diaconis and B.Sturmfels, Algebraic algorithms for sampling from
      conditional distributions, Annals of Statistics, 26, (1998) 363--397".
     4ti2 is an efficient implementation of this algorithm.
     The function oxm.markov calls the 4ti2 through an OpenXM server.
     In order to set up your own server,
     please refer to \url{http://www.openxm.org.}
     The function utilizes \code{\link{oxm.matrix_r2tfb}} and
     \code{\link[RCurl]{postForm}}.
 }  }
 \value{  \value{
 %%  ~Describe the value returned  The output is given by a list with the following named entries.
 %%  If it is a LIST, use    \item{markov}{Markov basis in a list.}
 %%  \item{comp1 }{Description of 'comp1'}    \item{text}{The string returned from the server. It is used to get errors.}
 %%  \item{comp2 }{Description of 'comp2'}  
 %% ...  
 }  }
 \references{  \references{
 %% ~put references to the literature/web site here ~    \url{http://www.4ti2.de}
   
     P.Diaconis and B.Sturmfels (1998), Algebraic algorithms for sampling from
     conditional distributions, Annals of Statistics, 26, 363--397.
 }  }
 \author{  \author{
 %%  ~~who you are~~  %%
 }  }
 \note{  \note{
 %%  ~~further notes~~  %%  ~~further notes~~
Line 39  oxm.markov(mat)
Line 60  oxm.markov(mat)
 %% ~Make other sections like Warning with \section{Warning }{....} ~  %% ~Make other sections like Warning with \section{Warning }{....} ~
   
 \seealso{  \seealso{
 %% ~~objects to See Also as \code{\link{help}}, ~~~  \code{\link{oxm.matrix_r2tfb}}
 }  }
 \examples{  \examples{
 ##---- Should be DIRECTLY executable !! ----  ## =====================================================
 ##-- ==>  Define data, use random,  ## Example 1. Markov basis of 2 x 3 contingency table.
 ##--    or do  help(data=index)  for the standard data sets.  ## =====================================================
   mat<-matrix(c(1,0,0,0, 1,0,1,0, 1,0,0,1,
 ## The function is currently defined as                1,1,0,0, 1,1,1,0, 1,1,0,1),nrow=4,ncol=6)
 function(mat) { return(mat); }  mb<-oxm.markov(mat)
   mb$markov
 }  }
 % Add one or more standard keywords, see file 'KEYWORDS' in the  % Add one or more standard keywords, see file 'KEYWORDS' in the
 % R documentation directory.  % R documentation directory.
 \keyword{ ~kwd1 }  \keyword{ Markov basis }
 \keyword{ ~kwd2 }% __ONLY ONE__ keyword per line  \keyword{ 4ti2 }
   \keyword{ OpenXM }
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