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fdaMocca  

Model-Based Clustering for Functional Data with Covariates
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("fdaMocca", "0.1-1")



Attach the package and use:
library("fdaMocca")
Maintained by
Natalya Pya Arnqvist
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-10-21
Latest Update: 2022-07-21
Description:
Routines for model-based functional cluster analysis for functional data with optional covariates. The idea is to cluster functional subjects (often called functional objects) into homogenous groups by using spline smoothers (for functional data) together with scalar covariates. The spline coefficients and the covariates are modelled as a multivariate Gaussian mixture model, where the number of mixtures corresponds to the number of clusters. The parameters of the model are estimated by maximizing the observed mixture likelihood via an EM algorithm (Arnqvist and Sj
How to cite:
Natalya Pya Arnqvist (2021). fdaMocca: Model-Based Clustering for Functional Data with Covariates. R package version 0.1-1, https://cran.r-project.org/web/packages/fdaMocca
Previous versions and publish date:
0.1-0 (2021-10-21 19:40)
Other packages that cited fdaMocca R package
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Other R packages that fdaMocca depends, imports, suggests or enhances
Functions, R codes and Examples using the fdaMocca R package
Some associated functions: criteria.mocca . estimate.mocca . fdaMocca-package . logLik.mocca . mocca . plot.mocca . print.mocca . simdata . summary.mocca . varve . 
Some associated R codes: Full fdaMocca package functions and examples
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