knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

mixRSVP

mixRSVP mixture models temporal errors in reports of an item from an array or a stream, presently using a mixture model of uniform and Gaussian distributions. Here is an explanation of what that means.

Installation

install_packages('devtools')  #if you don't have devtools already
library('devtools') 
#devtools::install_github('alexholcombe/mixRSVP',build_vignettes=TRUE) #No longer works
#Because of a change in devtools, you have to do this long command below to get the vignettes built
devtools::install_github('alexholcombe/mixRSVP', build = TRUE, build_opts = c("--no-resave-data", "--no-manual"))

Example

Fit some of one of the provided datasets and plot the histogram of serial position errors together with the fitted curve.

 df <-  subset(P2E2pilot, subject=="CB" & target==1 & condition==1)
 plot_hist_with_fit(df, -11, 11, df$targetSP, 16, TRUE, TRUE, TRUE)

Help

Type ?mixRSVP or ?<FUNCTIONNAME> and look at the vignettes that show examples of what you can do.

vignette(package='mixRSVP')

To-do

Still get warnings indicating pnorm is called with negative sigma, "Got NaN as a result of calling pnorm with: 0.5 3.66418579969812 -9.1e-05" Don't know why because sigma given bounds that greater than zero. Maybe function fitter still goes outside the bounds slight, and tightening the bounds will fix this?

Also get: "Error in eigen(nhatend) : infinite or missing values in 'x'"

History

Patrick Goodbourn programmed mixture modeling of RSVP serial position errors in MATLAB. Certifiedwaif did initial port of this to R, largely using automated code translation, and then Alex functionfied and improved things before making it into this package.



alexholcombe/mixRSVP documentation built on June 7, 2019, 3:50 p.m.