Maximum a posteriori (MAP) Classification

Description

MAP obtains maximum a posteriori (MAP) classifications. unMAP converts a classification vector into an indicator matrix.

Usage

MAP(mat, tie = c("random", "standard"))
unMAP(vec)

Arguments

Details

For each row in mat, MAP assigns an indexing value identifying the entry in the row taking the highest value. In the case where multiple values in a row share a common largest value, tie determines how such a value is chosen. If tie = "random", one of the suitable values is chosen at random; when tie = "standard", the first such suitable value is selected, in common with other packages. Defaults to "random".

Value

MAP returns a classification vector. unMAP returns a classification matrix, with each row indicating group membership by the column entry which is non-zero (and equal to one).

Author(s)

Arthur White

See Also

Zscore

Examples

##Simple example
s1<- sample(1:2, 10, replace=TRUE)
unMAP(s1)
MAP(unMAP(s1))

##More to the point
data(Alzheimer)
fit<- blca.em(Alzheimer, 2)
MAP(fit$Z) ## Best estimates of group membership. 

mat1<- matrix(1/3, nrow=10, ncol=3) ##demonstrating the use of "tie" argument
MAP(mat1, tie="random")
MAP(mat1, tie="standard")

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(BayesLCA)
Loading required package: e1071
Loading required package: coda
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/BayesLCA/MAP.Rd_%03d_medium.png", width=480, height=480)
> ### Name: MAP
> ### Title: Maximum _a posteriori_ (MAP) Classification
> ### Aliases: MAP unMAP
> ### Keywords: map unmap
> 
> ### ** Examples
> 
> ##Simple example
> s1<- sample(1:2, 10, replace=TRUE)
> unMAP(s1)
      [,1] [,2]
 [1,]    1    0
 [2,]    1    0
 [3,]    1    0
 [4,]    0    1
 [5,]    1    0
 [6,]    0    1
 [7,]    0    1
 [8,]    1    0
 [9,]    0    1
[10,]    1    0
> MAP(unMAP(s1))
 [1] 1 1 1 2 1 2 2 1 2 1
> 
> ##More to the point
> data(Alzheimer)
> fit<- blca.em(Alzheimer, 2)
Restart number 1, logpost = -749.43... 
Restart number 2, logpost = -749.44... 
Restart number 3, logpost = -749.44... 
Restart number 4, logpost = -749.44... 
Restart number 5, logpost = -749.44... 
> MAP(fit$Z) ## Best estimates of group membership. 
 [1] 1 1 1 1 1 2 1 2 1 1 1 2 2 2 1 1 1 2 1 2 2 1 2 1 2 2 2 2 1 1 2 2 1 1 2 2 2 2
[39] 2
> 
> mat1<- matrix(1/3, nrow=10, ncol=3) ##demonstrating the use of "tie" argument
> MAP(mat1, tie="random")
[1] "Some observations mapped to more than one group - these will be chosen at random."
 [1] 2 3 1 3 2 1 1 2 1 2
> MAP(mat1, tie="standard")
 [1] 1 1 1 1 1 1 1 1 1 1
Warning messages:
1: In map1[ind] <- M[mat[ind, ] == maxmat[ind]] :
  number of items to replace is not a multiple of replacement length
2: In map1[ind] <- M[mat[ind, ] == maxmat[ind]] :
  number of items to replace is not a multiple of replacement length
3: In map1[ind] <- M[mat[ind, ] == maxmat[ind]] :
  number of items to replace is not a multiple of replacement length
4: In map1[ind] <- M[mat[ind, ] == maxmat[ind]] :
  number of items to replace is not a multiple of replacement length
5: In map1[ind] <- M[mat[ind, ] == maxmat[ind]] :
  number of items to replace is not a multiple of replacement length
6: In map1[ind] <- M[mat[ind, ] == maxmat[ind]] :
  number of items to replace is not a multiple of replacement length
7: In map1[ind] <- M[mat[ind, ] == maxmat[ind]] :
  number of items to replace is not a multiple of replacement length
8: In map1[ind] <- M[mat[ind, ] == maxmat[ind]] :
  number of items to replace is not a multiple of replacement length
9: In map1[ind] <- M[mat[ind, ] == maxmat[ind]] :
  number of items to replace is not a multiple of replacement length
10: In map1[ind] <- M[mat[ind, ] == maxmat[ind]] :
  number of items to replace is not a multiple of replacement length
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>