R: STAPLE on Multi-class matrix

staple_multi_mat {stapler} | R Documentation

## STAPLE on Multi-class matrix

### Description

STAPLE on Multi-class matrix

### Usage

    staple_multi_mat(x, sens_init = 0.99999, spec_init = 0.99999,
      max_iter = 10000, tol = .Machine$double.eps, prior = "mean",
      verbose = TRUE, trace = 25, ties.method = c("first", "random", "last"))

### Arguments

`x` | a nxr matrix where there are n raters and r elements rated
`sens_init` | Initialize matrix for sensitivity (p)
`spec_init` | Initialize matrix for specificity (q)
`max_iter` | Maximum number of iterations to run
`tol` | Tolerance for convergence
`prior` | Either "mean" or a matrix of prior probabilities,
`verbose` | print diagnostic messages
`trace` | Number for modulus to print out verbose iterations
`ties.method` | Method passed to `max.col` for hard segmentation

### Value

List of matrix output sensitivities, specificities, and matrix of probabilities

### Examples

    rm(list = ls())
    x = matrix(rbinom(5000, size = 5, prob = 0.5), ncol = 1000)
      sens_init = 0.99999
      spec_init = 0.99999
      max_iter = 10000
      tol = .Machine$double.eps
      prior = "mean"
      verbose = TRUE
      trace = 25
      ties.method = "first"

    res = staple_multi_mat(x)

[Package stapler version 0.6.5 Index]