R/example.R

In wrbrooks/latent: Estimate the parameters of a Poisson latent variable model with left-censoring

#' An  example illustrating the function of packace latent
#' 
#' Estimates a latent contamination variable for the storm sewer data, using EM to impute censored values
#' 
#' @return latent a list as returned by function \code{\link{latent}}
#' 
#' @export
example <- function() {
    #---------
    # This script is an example of using the latent package to 
    # estimate the parameters of a latent variable model for the
    # FIB counts in the storm sewer data set (with event 3 removed).
    # Note that the data is automatically lazy-loaded, so no call
    # to data(...) is necessary.
    
    # Drop event 3, change mei[4] from "TNTC" to 0, and then convert all FIB to numerics:
    indx = which(dfOptAnalysisDataSSJan2015$Event != "03")
    fib = dfOptAnalysisDataSSJan2015[indx, c("mei", "modmtec", "FC", "Bac.human", "Lachno.2")]
    fib$mei[4] = 0
    for (n in names(fib))
        fib[[n]] = as.numeric(fib[[n]])
    
    # Set the censoring values for each of the FIB (these are guesstimates)
    min.detect = c('mei'=1, 'modmtec'=1, 'FC'=1, 'Bac.human'=225, 'Lachno.2'=225)
    
    # The human-specific FIB are Bac.human and Lachno.2, which are the fourth and fifth columns
    specific = c(FALSE, FALSE, FALSE, TRUE, TRUE)
    
    # Get the event IDs
    event = as.integer(dfOptAnalysisDataSSJan2015$Event[indx])
    
    # Now estimate the model parameters:
    latent(fib, min.detect, event, specific)
}