R/distributionise.R

In mkao006/sws_flag: Package to manipulate and aggregate observational status

##' This function converts the calculated parameter from the function
##' "paramerise" and create the distribution.
##'
##' @param obsValue The observed value
##' @param selfInformation The self information of the value, which is
##' defined as the negative log of the probability of the observed value.
##' @param distribution The distribution to be parameterised.
##'
##' @return A list containing the distribution function and the
##' parameters associated with the distribution
##'
##' @export

distributionise = function(obsValue, selfInformation, distribution){
    parameters = parameterise(obsValue = obsValue,
        selfInformation = selfInformation, distribution = distribution)
    if(selfInformation == 0){
        ## NOTE (Michael): We don't provide the real degenerate
        ##                 distribution as it may result in numerical
        ##                 error for the balancing mechanism.
        list(pdf = with(parameters, function(x) ifelse(x == k0, 1, 1e-100)),
             parameters = parameters)
    } else {
        switch(distribution,
               `normal` = {
                   list(pdf = with(parameters,
                            function(x) dnorm(x, mean = mean, sd = sd)),
                        parameters = parameters)
               },
               `cauchy` = {
                   list(pdf = with(parameters,
                            function(x) dcauchy(x, location = location,
                                                scale = scale)),
                        parameters = parameters)
               },
               `laplace` = {
                   list(pdf = with(parameters,
                            function(x) dlaplace(x, location = location, scale = scale)),
                        parameters = parameters)
               },
               `truncNorm` = {
                   list(pdf = with(parameters,
                            function(x) dtruncnorm(x, a = 0, b = Inf, mean = mean,
                                                   sd = sd)),
                        parameters = parameters)
               },
               `logNorm` = {
                   list(pdf = with(parameters,
                            function(x) dlnorm(x, meanlog = meanlog, sdlog = sdlog)),
                        parameters = parameters)
               },
               `exponential` = {
                   list(pdf = with(parameters, function(x) dexp(x, rate = rate)),
                        parameters = parameters)
               },
               `weibull` = {
                   list(pdf = with(parameters,
                            function(x) dweibull(x, shape = shape, scale = scale)),
                        parameters = parameters)
               }
               )
    }
}