Package: BNPdensity 2023.3.8

Guillaume Kon Kam King

BNPdensity: Ferguson-Klass Type Algorithm for Posterior Normalized Random Measures

Bayesian nonparametric density estimation modeling mixtures by a Ferguson-Klass type algorithm for posterior normalized random measures.

Authors:Julyan Arbel [ctb], Ernesto Barrios [aut], Guillaume Kon Kam King [aut, cre], Antonio Lijoi [aut], Luis E. Nieto-Barajas [aut], Igor Prünster [aut]

BNPdensity_2023.3.8.tar.gz
BNPdensity_2023.3.8.tar.gz(r-4.5-noble)BNPdensity_2023.3.8.tar.gz(r-4.4-noble)
BNPdensity_2023.3.8.tgz(r-4.4-emscripten)BNPdensity_2023.3.8.tgz(r-4.3-emscripten)
BNPdensity.pdf |BNPdensity.html✨
BNPdensity/json (API)

# Install 'BNPdensity' in R:
install.packages('BNPdensity', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

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This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.89 score 78 scripts 430 downloads 18 exports 40 dependencies

Last updated 2 years agofrom:314c943b35. Checks:OK: 1 NOTE: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 18 2024
R-4.5-linuxNOTENov 18 2024

Exports:compute_optimal_clusteringcpoexpected_number_of_components_Dirichletexpected_number_of_components_stableGOFplotsMixNRMI1MixNRMI1censMixNRMI2MixNRMI2censMixPY1MixPY2multMixNRMI1multMixNRMI1censmultMixNRMI2multMixNRMI2censplot_clustering_and_CDFplot_prior_number_of_componentstraceplot

Dependencies:clicodacolorspacecpp11dplyrfansifarvergenericsggplot2gluegridExtragtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigpurrrR6RColorBrewerrlangscalesstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Bayesian nonparametric density estimationBNPdensity-package BNPdensity
Acidity Index Datasetacidity
Add x and yadd
Convert the output of multMixNRMI into a coda mcmc objectas.mcmc.multNRMI
If the function Rmpfr::asNumeric returns a warning about inefficiency, silence it.asNumeric_no_warning
Comment on the NRMI process depending on the value of the parameterscomment_on_NRMI_type
Compute the optimal clustering from an MCMC samplecompute_optimal_clustering
Compute the grid for thinning the MCMC chaincompute_thinning_grid
Convert the output of multMixNRMI into a coda mcmc objectconvert_to_mcmc
Extract the Conditional Predictive Ordinates (CPOs) from a list of fitted objectscpo.multNRMI
Extract the Conditional Predictive Ordinates (CPOs) from a fitted objectcpo.NRMI1
Extract the Conditional Predictive Ordinates (CPOs) from a fitted objectcpo.NRMI2
Convert distribution names to indicesdist_name_k_index_converter
Non-standard student-t densitydt_
Enzyme Datasetenzyme
Fit of MixNRMI1 function to the enzyme datasetEnzyme1.out
Fit of MixNRMI2 function to the enzyme datasetEnzyme2.out
Computes the expected number of components for a Dirichlet process.expected_number_of_components_Dirichlet
Computes the expected number of components for a stable process.expected_number_of_components_stable
Repeat the common scale parameter of a semiparametric model to match the dimension of the location parameters.fill_sigmas
Galaxy Data Setgalaxy
Fit of MixNRMI1 function to the galaxy datasetGalaxy1.out
Fit of MixNRMI2 function to the galaxy datasetGalaxy2.out
Gives the kernel name from the integer codegive_kernel_name
Plot Goodness of fits graphical checks for censored dataGOFplots
Plot Goodness of fits graphical checks for censored dataGOFplots_censored
Plot Goodness of fits graphical checks for non censored dataGOFplots_noncensored
Create a plotting grid from censored or non-censored data.grid_from_data
Create a plotting grid from censored data.grid_from_data_censored
Create a plotting grid from non-censored data.grid_from_data_noncensored
Test if the data is censoredis_censored
Tests if a fit is a semi parametric or nonparametric model.is_semiparametric
Normalized Random Measures Mixture of Type IMixNRMI1
Normalized Random Measures Mixture of Type I for censored dataMixNRMI1cens
Normalized Random Measures Mixture of Type IIMixNRMI2
Normalized Random Measures Mixture of Type II for censored dataMixNRMI2cens
Pitman-Yor process mixture of Type IMixPY1
Pitman-Yor process mixture of Type IIMixPY2
Multiple chains of MixNRMI1multMixNRMI1
Multiple chains of MixNRMI1censmultMixNRMI1cens
Multiple chains of MixNRMI2multMixNRMI2
Multiple chains of MixNRMI2censmultMixNRMI2cens
Invert jump heights functionMvInv
Plot the clustering and the Cumulative Distribution Functionplot_clustering_and_CDF
This plots the prior distribution on the number of components for the stable process. The Dirichlet process is provided for comparison.plot_prior_number_of_components
Plot the density estimate and the 95% credible intervalplot.multNRMI
Plot the density estimate and the 95% credible intervalplot.NRMI1
Plot the density estimate and the 95% credible intervalplot.NRMI2
Plot the density estimate and the 95% credible intervalplot.PY1
Plot the density estimate and the 95% credible intervalplot.PY2
Plot the Turnbull CDF and fitted CDF for censored data.plotCDF_censored
Plot the empirical and fitted CDF for non censored data.plotCDF_noncensored
Plot the density estimate and the 95% credible interval for censored dataplotfit_censored
Plot the density estimate and the 95% credible interval for noncensored dataplotfit_noncensored
Plot the density for censored data.plotPDF_censored
Plot the density and a histogram for non censored data.plotPDF_noncensored
Plot the percentile-percentile graph for non censored data, using the Turnbull estimator the position of the percentiles.pp_plot_censored
Plot the percentile-percentile graph for non censored data.pp_plot_noncensored
S3 method for class 'multNRMI'print.multNRMI
S3 method for class 'MixNRMI1'print.NRMI1
S3 method for class 'MixNRMI2'print.NRMI2
S3 method for class 'PY1'print.PY1
S3 method for class 'PY2'print.PY2
Process the distribution name argument into a distribution indexprocess_dist_name
Plot the quantile-quantile graph for censored data.qq_plot_censored
Plot the quantile-quantile graph for non censored data.qq_plot_noncensored
Salinity tolerancesalinity
S3 method for class 'multNRMI'summary.multNRMI
S3 method for class 'MixNRMI1'summary.NRMI1
S3 method for class 'MixNRMI2'summary.NRMI2
S3 method for class 'PY1'summary.PY1
S3 method for class 'PY2'summary.PY2
Common text for the summary S3 methodssummarytext
Draw a traceplot for multiple chainstraceplot