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RMLPCA
View on CRAN: Click
here
Download and install RMLPCA package within the R console
Install from CRAN:
install.packages("RMLPCA")
Install from Github:
library("remotes")
install_github("cran/RMLPCA")
Install by package version:
library("remotes")
install_version("RMLPCA", "0.0.1")
Attach the package and use:
library("RMLPCA")
Maintained by
Renan Santos Barbosa
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-11-05
Latest Update: 2020-11-05
Description:
R implementation of Maximum Likelihood Principal Component Analysis
The main idea of this package is to have an alternative way of PCA for
subspace modeling that considers measurement errors.
More details can be found in Peter D. Wentzell (2009)
.
How to cite:
Renan Santos Barbosa (2020). RMLPCA: Maximum Likelihood Principal Component Analysis. R package version 0.0.1, https://cran.r-project.org/web/packages/RMLPCA. Accessed 30 Jan. 2025.
Previous versions and publish date:
No previous versions
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Other R packages that RMLPCA depends,
imports, suggests or enhances
Complete documentation for RMLPCA
Functions, R codes and Examples using
the RMLPCA R package
Some associated functions: RMLPCA . cov_d . cov_e . data_clean . data_clean_e . data_cleaned_mlpca_b . data_cleaned_mlpca_c . data_cleaned_mlpca_d . data_cleaned_mlpca_e . data_error_b . data_error_c . data_error_d . data_error_e . mlpca_b . mlpca_c . mlpca_d . mlpca_e . sds_b . sds_c .
Some associated R codes: RMLPCA.R . cov_d.R . cov_e.R . data_clean.R . data_clean_e.R . data_cleaned_mlpca_b.R . data_cleaned_mlpca_c.R . data_cleaned_mlpca_d.R . data_cleaned_mlpca_e.R . data_error_b.R . data_error_c.R . data_error_d.R . data_error_e.R . mlpca_b.R . mlpca_c.R . mlpca_d.R . mlpca_e.R . sds_b.R . sds_c.R . Full RMLPCA package functions and examples
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