Aggregated individual judgements (AIJ) slot

Description

AIJ (Aggregated individual judgements) is a slot of geoAggreg class. It consists of a matrix of aggregated group judgements (a pairwise comparison matrix).

Author(s)

Daryanaz Dargahi <daryanazdargahi@gmail.com>

Examples

mat <- matrix(nrow = 4, ncol = 1, data = NA)
mat[,1] <- c(system.file('extdata','ind1.tsv',package = 'Prize'),
            system.file('extdata','ind2.tsv',package = 'Prize'),
            system.file('extdata','ind3.tsv',package = 'Prize'),
            system.file('extdata','ind4.tsv',package = 'Prize'))
rownames(mat) <- c('ind1','ind2','ind3', 'ind4')
colnames(mat) <- c('individual_judgement')

# non-weighted aggregation
res <- gaggregate(srcfile = mat, method = 'geometric', simulation = 500)
AIJ(res)

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(Prize)
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/Prize/AIJ.Rd_%03d_medium.png", width=480, height=480)
> ### Name: AIJ
> ### Title: Aggregated individual judgements (AIJ) slot
> ### Aliases: AIJ aij Aij AIJ,ANY-method
> 
> ### ** Examples
> 
> mat <- matrix(nrow = 4, ncol = 1, data = NA)
> mat[,1] <- c(system.file('extdata','ind1.tsv',package = 'Prize'),
+             system.file('extdata','ind2.tsv',package = 'Prize'),
+             system.file('extdata','ind3.tsv',package = 'Prize'),
+             system.file('extdata','ind4.tsv',package = 'Prize'))
> rownames(mat) <- c('ind1','ind2','ind3', 'ind4')
> colnames(mat) <- c('individual_judgement')
> 
> # non-weighted aggregation
> res <- gaggregate(srcfile = mat, method = 'geometric', simulation = 500)
Reading individual judgements.
Aggregating individual judgements with geometric mean (AIJ).
Computing group consistency ratio (GCR).
Computing consensus index (CI).
> AIJ(res)
                  Tumor_expression Normal_expression Frequency Epitopes
Tumor_expression         1.0000000         2.0000000 3.4641016 5.143687
Normal_expression        0.5000000         1.0000000 3.6628415 5.383563
Frequency                0.2886751         0.2730121 1.0000000 1.681793
Epitopes                 0.1944131         0.1857506 0.5946036 1.000000
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>