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multimix
View on CRAN: Click
here
Download and install multimix package within the R console
Install from CRAN:
install.packages("multimix")
Install from Github:
library("remotes")
install_github("cran/multimix")
Install by package version:
library("remotes")
install_version("multimix", "1.0-10")
Attach the package and use:
library("multimix")
Maintained by
James Curran
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-01-18
Latest Update: 2023-01-18
Description:
A set of functions which use the Expectation Maximisation (EM)
algorithm (Dempster, A. P., Laird, N. M., and Rubin, D. B. (1977)
Maximum likelihood from
incomplete data via the EM algorithm, Journal of the Royal Statistical
Society, 39(1), 1--22) to take a finite mixture model approach to
clustering. The package is designed to cluster multivariate data that have
categorical and continuous variables and that possibly contain missing
values. The method is described in Hunt, L. and Jorgensen, M. (1999)
Australian & New Zealand Journal of Statistics
41(2), 153--171 and Hunt, L. and Jorgensen, M. (2003)
Mixture model clustering for mixed data
with missing information, Computational Statistics & Data Analysis, 41(3-4),
429--440.
How to cite:
James Curran (2023). multimix: Fit Mixture Models Using the Expectation Maximisation (EM) Algorithm. R package version 1.0-10, https://cran.r-project.org/web/packages/multimix. Accessed 22 Dec. 2024.
Previous versions and publish date:
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Other R packages that multimix depends,
imports, suggests or enhances
Complete documentation for multimix
Functions, R codes and Examples using
the multimix R package
Some associated functions: cancer.df . cmc.df . count.unique . data_organise . eStep . initParamList . left . mStep . make_Z_discrete . make_Z_fortran . make_Z_random . mmain . multimix-package . pair.index . plot.multimixResults . print.multimixParamList . print.multimixResults . right .
Some associated R codes: data.R . eStep.R . initParamList.R . multimix-package.R . plot.multimixResults.R . print.multimixParamList.R . print.multimixResults.R . setNames.R . Full multimix package functions and examples
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