MPS: An R package for modelling shifted families of distributions

SummaryGeneralised statistical distributions have been widely used over the last decades for modelling phenomena in different fields. The generalisations have been made to produce distributions with more flexibility and lead to more accurate modelling in practice. Statistical analysis of the generalised distributions requires new statistical packages. TheNewdistns package due to Nadarajah and Rocha providesR routines with functionality to compute probability density function (PDF), cumulative distribution function (CDF), quantile function, random numbers and parameter estimates of 19 families of distributions with applications in survival analysis. Here, we introduce anR package, calledMPS, for computing PDF, CDF, quantile function, random numbers, Q –Q plots and parameter estimates for 24 shifted new families of distributions. By considering an extra location parameter, each family will be defined on the whole real line and so covers a broader range of applicability. We adopt the well-known maximum product spacing approach to estimate paramet ers of the families because under some situations the maximum likelihood (ML) estimators fail to exist. We demonstrateMPS by analysing two well-known real data sets. For the first data set, the ML estimators break down, butMPS works well. For the second set, adding a location parameter results in a reasonable model while the absence of the location parameter makes the model quite inappropriate. TheMPS is available from CRAN athttps://...
Source: Australian and New Zealand Journal of Statistics - Category: Statistics Authors: Tags: Original Article Source Type: research