In YunranChen/prml: An Implementation of PRML Classifier and PRML Filter

knitr::opts_chunk$set(echo = TRUE)

Overview

This package is designed to implement the PRML classifier and PRML filter proposed by Chen and Tokdar (2019).

• prml_filter() calculate Bayes factor of Poisson versus Poisson mixtures.
• prml_classifier() calculate posterior probabilities under each Poisson mixtures hypotheses.
• prml_classifier_f() calculate posterior probabilities under each Poisson mixtures hypotheses and density estimation of mixing density.
• prml_tests() output the result of PRML classifier prml_classifier() as well as PRML filter prml_filter()
• prml_tests_f() output the result of PRML classifier prml_classifier_f() as well as PRML filter prml_filter()

For real data anlaysis, we only need to use function prml_tests(), which take the ${Y^A,Y^B,Y^{AB}}$ as input. ${Y^A,Y^B,Y^{AB}}$ represent spike count data coming from the repeated trials under condition ${A,B,AB}$ (single-stimulus trial A, B and dual-stimuli trial AB). We provide a sample code on

• (1) how to extract the spike count triplets from the raw data;
• (2) how to use function prml_tests();
• (3) simple data visualization on the result.

If you want to obtain density estimation of the mixing density, replace prml_tests() with prml_tests_f() in the sample code. See Articles for details.

Installation

Not yet available in cran. Install the development version for now.

install.packages("prml")

Development version

devtools::install_github("yunranchen/prml")

Result

A classification on the four possible hypotheses before PRML filtering and after PRML filtering process.

knitr::include_graphics("vignettes/images/plot.png")

A density estimation on the mixing density function. (Here only present the 'Mixture' and 'Intermediate' hypotheses.)

knitr::include_graphics("vignettes/images/plot_pdf.png")

YunranChen/prml documentation built on May 16, 2019, 4:06 a.m.