PAMA (version 0.1.1)

PAMA.F: This function implements Maximum Likelihood estimation of PAMA model.

Description

This function implements Maximum Likelihood estimation of PAMA model.

Usage

PAMA.F(datfile, nRe, threshold, iter = 1000)

Arguments

datfile

A matrix or dataframe. This is the data where our algorithm will work on. Each row denotes a ranker's ranking. The data should be in entity-based format.

nRe

A number. Number of relevant entities.

threshold

A number(positive). The stopping threshold in determining convergence of MLE. if the two consecutive iterations of log-likelihood is smaller than threshold, then the convergence achives.

iter

A number. Numner of iterations of MCMC.

Value

List. It contains MLE of all the parameters and log-likelihood.

1. I.mat: samples of I

2. phi.mat: samples of phi.

3. smlgamma.mat: samples of gamma

4. l.mat: samples of log-likelihood

Examples

# NOT RUN {
a=NBANFL()
PAMA.F(a$NBA,nRe=10,threshold=0.1,iter=100)
# }