BNPdensity2023.3.8 package

Ferguson-Klass Type Algorithm for Posterior Normalized Random Measures

add

Add x and y

as.mcmc.multNRMI

Convert the output of multMixNRMI into a coda mcmc object

asNumeric_no_warning

If the function Rmpfr::asNumeric returns a warning about inefficiency,...

BNPdensity-package

Bayesian nonparametric density estimation

cens_data_check

Censoring data check

censor_code_rl

Censor code right-left

comment_on_NRMI_type

Comment on the NRMI process depending on the value of the parameters

comp1

Ties function: univariate

comp2

Ties function: bivariate

compute_optimal_clustering

Compute the optimal clustering from an MCMC sample

compute_thinning_grid

Compute the grid for thinning the MCMC chain

convert_to_mcmc

Convert the output of multMixNRMI into a coda mcmc object

cpo.multNRMI

Extract the Conditional Predictive Ordinates (CPOs) from a list of fit...

cpo.NRMI1

Extract the Conditional Predictive Ordinates (CPOs) from a fitted obje...

cpo.NRMI2

Extract the Conditional Predictive Ordinates (CPOs) from a fitted obje...

cpo

Conditional predictive ordinate function

dhalfcauchy

Density half Cauchy

dhalfnorm

Density half normal

dhalft

Density half Student-t

dist_name_k_index_converter

Convert distribution names to indices

dk

Kernel density function

dkcens2

Density of the chosen kernel

dkcens2_1val

Density evaluation once

dt_

Non-standard student-t density

dtnorm

Density truncated normal

Enzyme1.out

Fit of MixNRMI1 function to the enzyme dataset

expected_number_of_components_Dirichlet

Computes the expected number of components for a Dirichlet process.

expected_number_of_components_stable

Computes the expected number of components for a stable process.

fcondXA

Conditional density evaluation in the semiparametric model

fcondXA2

Conditional density evaluation in the fully nonparametric model

fcondXA2cens2

Conditional density evaluation in the fully nonparametric model for ce...

fcondYXA

Conditional posterior distribution of the latents Y

fcondYXAcens2

Conditional posterior distribution of the latents Y in the censoring c...

fcondYZXA

Conditional posterior distribution of the bivariate latents (Y,Z)

fcondYZXAcens2

Conditional posterior distribution of the bivariate latents (Y,Z) in t...

fill_sigmas

Repeat the common scale parameter of a semiparametric model to match t...

give_kernel_name

Gives the kernel name from the integer code

GOFplots

Plot Goodness of fits graphical checks for censored data

GOFplots_censored

Plot Goodness of fits graphical checks for censored data

GOFplots_noncensored

Plot Goodness of fits graphical checks for non censored data

grid_from_data

Create a plotting grid from censored or non-censored data.

grid_from_data_censored

Create a plotting grid from censored data.

grid_from_data_noncensored

Create a plotting grid from non-censored data.

gs3

Conditional posterior distribution of latent U

gs3_adaptive3

Conditional posterior distribution of latent U

gs3_log

Conditional posterior distribution of latent logU

gs4

Resampling Ystar function

gs4cens2

Resampling Ystar function in the case of censoring

gs5

Conditional posterior distribution of sigma

gs5cens2

Conditional posterior distribution of sigma in the case of censoring

gsHP

Updates the hyper-parameters of py0

gsYZstar

Jointly resampling Ystar and Zstar function

gsYZstarcens2

Jointly resampling Ystar and Zstar function in the case of censoring

is_censored

Test if the data is censored

is_semiparametric

Tests if a fit is a semi parametric or nonparametric model.

logacceptance_ratio_logu

Metropolis-Hastings ratio for the conditional of logU

logdprop_logu

Contribution of the proposal kernel logdensity to the Metropolis-Hasti...

logf_logu_cond_y

Contribution of the target logdensity of logU to the Metropolis-Hastin...

logf_u_cond_y

Target logdensity of U given the data

MixNRMI1

Normalized Random Measures Mixture of Type I

MixNRMI1cens

Normalized Random Measures Mixture of Type I for censored data

MixNRMI2

Normalized Random Measures Mixture of Type II

MixNRMI2cens

Normalized Random Measures Mixture of Type II for censored data

MixPY1

Pitman-Yor process mixture of Type I

MixPY2

Pitman-Yor process mixture of Type II

multMixNRMI1

Multiple chains of MixNRMI1

multMixNRMI1cens

Multiple chains of MixNRMI1cens

multMixNRMI2

Multiple chains of MixNRMI2

multMixNRMI2cens

Multiple chains of MixNRMI2cens

Mv

Continuous Jump heights function

MvInv

Invert jump heights function

p0

Centering function

phalfcauchy

Distribution function half Cauchy

phalfnorm

Distribution function half Normal

phalft

Distribution function half Student-t

pk

Kernel distribution function

plot.multNRMI

Plot the density estimate and the 95% credible interval

plot.NRMI1

Plot the density estimate and the 95% credible interval

plot.NRMI2

Plot the density estimate and the 95% credible interval

plot.PY1

Plot the density estimate and the 95% credible interval

plot.PY2

Plot the density estimate and the 95% credible interval

plot_clustering_and_CDF

Plot the clustering and the Cumulative Distribution Function

plot_prior_number_of_components

This plots the prior distribution on the number of components for the ...

plotCDF_censored

Plot the Turnbull CDF and fitted CDF for censored data.

plotCDF_noncensored

Plot the empirical and fitted CDF for non censored data.

plotfit_censored

Plot the density estimate and the 95% credible interval for censored d...

plotfit_noncensored

Plot the density estimate and the 95% credible interval for noncensore...

plotPDF_censored

Plot the density for censored data.

plotPDF_noncensored

Plot the density and a histogram for non censored data.

pp_plot_censored

Plot the percentile-percentile graph for non censored data, using the ...

pp_plot_noncensored

Plot the percentile-percentile graph for non censored data.

print.multNRMI

S3 method for class 'multNRMI'

print.NRMI1

S3 method for class 'MixNRMI1'

print.NRMI2

S3 method for class 'MixNRMI2'

print.PY1

S3 method for class 'PY1'

print.PY2

S3 method for class 'PY2'

process_dist_name

Process the distribution name argument into a distribution index

pt_

Distribution function non-standard student-t

ptnorm

Distribution function truncated normal

qgeneric

Generic function to find quantiles of a distribution

qhalfcauchy

Quantile function half Cauchy

qhalfnorm

Quantile function half Normal

qhalft

Quantile function half Student-t

qq_plot_censored

Plot the quantile-quantile graph for censored data.

qq_plot_noncensored

Plot the quantile-quantile graph for non censored data.

qt_

Quantile function non-standard Student-t

qtnorm

Quantile function truncated normal

rfystar

Conditional posterior distribution of the distinct Ystar

rfystarcens2

Conditional posterior distribution of the distinct Ystar in the case o...

rfyzstar

Conditional posterior distribution of the distinct vectors (Ystar,Zsta...

rfyzstarcens2

Conditional posterior distribution of the distinct vectors (Ystar,Zsta...

rhalfcauchy

Random number generator half Cauchy

rhalfnorm

Random number generator half Normal

rhalft

Random number generator half Student-t

rk

Kernel density sampling function

rprop_logu

Proposal distribution for logU

rt_

Random number generator non-standard Student-t

rtnorm

Random number generator for a truncated normal distribution

summary.multNRMI

S3 method for class 'multNRMI'

summary.NRMI1

S3 method for class 'MixNRMI1'

summary.NRMI2

S3 method for class 'MixNRMI2'

summary.PY1

S3 method for class 'PY1'

summary.PY2

S3 method for class 'PY2'

summarytext

Common text for the summary S3 methods

thresholdGG

Choosing the truncation level for the NGG process

traceplot

Draw a traceplot for multiple chains

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

  • Maintainer: Guillaume Kon Kam King
  • License: GPL (>= 2)
  • Last published: 2023-03-24