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MixSemiRob (version 1.1.0)

Mixture Models: Parametric, Semiparametric, and Robust

Description

Various functions are provided to estimate parametric mixture models (with Gaussian, t, Laplace, log-concave distributions, etc.) and non-parametric mixture models. The package performs hypothesis tests and addresses label switching issues in mixture models. The package also allows for parameter estimation in mixture of regressions, proportion-varying mixture of regressions, and robust mixture of regressions.

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Version

Install

install.packages('MixSemiRob')

Monthly Downloads

145

Version

1.1.0

License

GPL (>= 2)

Maintainer

Suyeon Kang

Last Published

September 20th, 2023

Functions in MixSemiRob (1.1.0)

Kernel Density-based EM-type algorithm for Semiparametric Mixture Regression with Unspecified Error Distributions

Parameter Estimation of Normal Mixture Using EM Algorithm

Complete Likelihood Frequency Method for Label Switching

Euclidean Distance Based Labeling Method for Label Switching

Profile Likelihood Method for Normal Mixture with Unequal Variance

MLE of Mixture Regression with Normal Errors

Kernel Density-based EM-type algorithm for Semiparametric Mixture Regression with Unspecified Homogenous Error Distributions

Kernel Density-based EM-type algorithm with Least Square Estimation for Semiparametric Mixture Regression with Unspecified Homogenous Error Distributions

Two-component Normal Mixture Estimation with One Known Component

Continuous Scale Mixture Approach for Normal Scale Mixture Model

Clustering with Mixtures of Log-concave Distributions using EM Algorithm (Univariate)

Clustering with Mixtures of Log-concave Distributions using EM Algorithm (Multivariate)

Goodness of Fit Test for Finite Mixture Models

Robust Mixture Regression with Thresholding-Embedded EM Algorithm for Penalized Estimation

Semiparametric Mixture Model by Minimizing Profile Hellinger Distance

Semiparametric Mixture of Binomial Regression with a Degenerate Component with Constant Proportion and Time-Varying Success Probability (One-step Backfitting)

Semiparametric Mixture of Binomial Regression with a Degenerate Component with Constant Proportion and Time-Varying Success Probability (Backfitting)

Robust Mixture Regression with T-distribution

Robust Mixture Regression with Laplace Distribution

Robust EM Algorithm For Mixture of Linear Regression Based on Bisquare Function

Semiparametric Mixtures of Nonparametric Regressions with Global EM-type Algorithm

Semiparametric Mixtures of Nonparametric Regressions with Local EM-type Algorithm

Mixture of Regression Models with Varying Mixing Proportions

Varying Proportion Mixture Data Generator

Robust Regression Estimator Using Trimmed Likelihood

Tone perception data

Semiparametric Mixture Regression Models with Single-index Proportion and Fully Iterative Backfitting

Semiparametric Mixture of Binomial Regression with a Degenerate Component with Time-Varying Proportion and Time-Varying Success Probability

Parameter Estimation for Uni- or Multivariate Normal Mixture Models

Dimension Reduction Based on Sliced Inverse Regression

Semiparametric Mixture Data Generator

Semiparametric Mixture Regression Models with Single-index and One-step Backfitting