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nspmix (version 2.0-0)

Nonparametric and Semiparametric Mixture Estimation

Description

Mainly for maximum likelihood estimation of nonparametric and semiparametric mixture models, but can also be used for fitting finite mixtures. The algorithms are developed in Wang (2007) and Wang (2010) .

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Version

Install

install.packages('nspmix')

Monthly Downloads

222

Version

2.0-0

License

GPL (>= 2)

Maintainer

Yong Wang

Last Published

May 10th, 2025

Functions in nspmix (2.0-0)

Log-likleihood Extra Term.

Log-density and its derivative values

Derivative of the log-likleihood Extra Term

Class npnbinom

Log-likelihood value of a mixture

Plotting a Nonparametric or Semiparametric Normal Mixture

Plots a function for an object of class nspmix

Prints a discrete distribution function

Sorting of an Object of Class npnorm

Plot the Gradient Function

Plot a discrete distribution function

Lung Cancer Data

Plotting a nonparametric Poisson mixture

Illness Spells and Frequencies of Thai Preschool Children

Plotting a nonparametric geometric mixture

Valid parameter values

Toxoplasmosis Data

Plotting a nonparametric negative binomial mixture

Weighted Histograms Plots or computes the histogram with observations with multiplicities/weights. Just like hist, whist can either plot the histogram or compute the values that define the histogram, by setting plot to TRUE or FALSE. The histogram can either be the one for frequencies or density, by setting freq to TRUE or FALSE.

Sorting of an Object of Class nppois

Density function of a mixture distribution

Hierarchical Constrained Newton method

Initialization for a nonparametric/semiparametric mixture

Maximum Likelihood Estimation of a Nonparametric Mixture Model

Maximum Likelihood Estimation of a Semiparametric Mixture Model

Beta-blockers Data

Z-values of BRCA Data