Other packages > Find by keyword >

MGMM  

Missingness Aware Gaussian Mixture Models
View on CRAN: Click here


Download and install MGMM package within the R console
Install from CRAN:
install.packages("MGMM")

Install from Github:
library("remotes")
install_github("cran/MGMM")

Install by package version:
library("remotes")
install_version("MGMM", "1.0.1.1")



Attach the package and use:
library("MGMM")
Maintained by
Zachary McCaw
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-08-26
Latest Update: 2023-09-30
Description:
Parameter estimation and classification for Gaussian Mixture Models (GMMs) in the presence of missing data. This package complements existing implementations by allowing for both missing elements in the input vectors and full (as opposed to strictly diagonal) covariance matrices. Estimation is performed using an expectation conditional maximization algorithm that accounts for missingness of both the cluster assignments and the vector components. The output includes the marginal cluster membership probabilities; the mean and covariance of each cluster; the posterior probabilities of cluster membership; and a completed version of the input data, with missing values imputed to their posterior expectations. For additional details, please see McCaw ZR, Julienne H, Aschard H. "Fitting Gaussian mixture models on incomplete data." .
How to cite:
Zachary McCaw (2020). MGMM: Missingness Aware Gaussian Mixture Models. R package version 1.0.1.1, https://cran.r-project.org/web/packages/MGMM
Previous versions and publish date:
0.3.1 (2020-08-26 13:50), 0.4.0 (2021-07-25 16:50), 1.0.0 (2021-12-21 19:12), 1.0.1 (2023-08-08 15:50)
Other packages that cited MGMM R package
View MGMM citation profile
Other R packages that MGMM depends, imports, suggests or enhances
Downloads during the last 30 days
Get rewarded with contribution points by helping add
Reviews / comments / questions /suggestions ↴↴↴

Today's Hot Picks in Authors and Packages

steepness  
Testing Steepness of Dominance Hierarchies
The steepness package computes steepness as a property of dominance hierarchies. Steepness is define ...
Download / Learn more Package Citations See dependency  
rdbnomics  
Download DBnomics Data
R access to hundreds of millions data series from DBnomics API (). ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
ftaproxim  
Fault Tree Analysis Based on Proxel Simulation
Calculation and plotting of instantaneous unavailabilities of basic events along with the top event ...
Download / Learn more Package Citations See dependency  
mistral  
Methods in Structural Reliability
Various reliability analysis methods for rare event inference (computing failure probability and qua ...
Download / Learn more Package Citations See dependency  
critpath  
Setting the Critical Path in Project Management
Solving the problem of project management using CPM (Critical Path Method), PERT (Program Evaluation ...
Download / Learn more Package Citations See dependency  

22,114

R Packages

188,080

Dependencies

55,244

Author Associations

22,115

Publication Badges

© Copyright 2022 - present. All right reserved, rpkg.net. Contact Us / Suggestions / Concerns