Package: fdaMocca 0.1-1
Natalya Pya Arnqvist
fdaMocca: Model-Based Clustering for Functional Data with Covariates
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 Sjöstedt de Luna, 2019) <arxiv:1904.10265>. The clustering method is used to analyze annual lake sediment from lake Kassjön (Northern Sweden) which cover more than 6400 years and can be seen as historical records of weather and climate.
Authors:
fdaMocca_0.1-1.tar.gz
fdaMocca_0.1-1.tar.gz(r-4.5-noble)fdaMocca_0.1-1.tar.gz(r-4.4-noble)
fdaMocca_0.1-1.tgz(r-4.4-emscripten)fdaMocca_0.1-1.tgz(r-4.3-emscripten)
fdaMocca.pdf |fdaMocca.html✨
fdaMocca/json (API)
# Install 'fdaMocca' in R: |
install.packages('fdaMocca', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- simdata - Simulated data
- simdata0 - Simulated data
- varve - Varved sediment data from lake Kassjön
- varve_full - Varved sediment data from lake Kassjön
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:bea75947b7. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 28 2024 |
R-4.5-linux | OK | Nov 28 2024 |
Exports:criteria.moccaestimate.moccalogLik.moccamoccaplot.moccaprint.moccaprint.summary.moccasummary.mocca
Dependencies:ashbitopscliclustercodetoolscolorspacedeSolvedoParallelfansifarverfdafdsFNNforeachggplot2gluegtablehdrcdeisobanditeratorskernlabKernSmoothkslabelinglatticelifecyclelocfitmagrittrMASSMatrixmclustmgcvmulticoolmunsellmvtnormnlmepcaPPpillarpkgconfigpracmaR6rainbowRColorBrewerRcppRCurlrlangscalestibbleutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Model-based clustering for functional data with covariates | fdaMocca-package |
AIC, BIC, entropy for a functional clustering model | criteria.mocca |
Model parameter estimation | estimate.mocca |
Log-likelihood for a functional clustering model | logLik.mocca |
Model-based clustering for functional data with covariates | mocca |
mocca plotting | plot.mocca |
Print a mocca object | print.mocca |
Simulated data | simdata simdata0 |
Summary for a mocca fit | print.summary.mocca summary.mocca |
Varved sediment data from lake Kassjön | varve varve_full |