acidity | Acidity Index Dataset |
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... |
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... |
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 | Conditional predictive ordinate function |
cpo.multNRMI | Extract the Conditional Predictive Ordinates (CPOs) from a... |
cpo.NRMI1 | Extract the Conditional Predictive Ordinates (CPOs) from a... |
cpo.NRMI2 | Extract the Conditional Predictive Ordinates (CPOs) from a... |
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 |
enzyme | Enzyme Dataset |
Enzyme1.out | Fit of MixNRMI1 function to the enzyme dataset |
Enzyme2.out | Fit of MixNRMI2 function to the enzyme dataset |
expected_number_of_components_Dirichlet | Computes the expected number of components for a Dirichlet... |
expected_number_of_components_stable | Computes the expected number of components for a stable... |
fcondXA | Conditional density evaluation in the semiparametric model |
fcondXA2 | Conditional density evaluation in the fully nonparametric... |
fcondXA2cens2 | Conditional density evaluation in the fully nonparametric... |
fcondYXA | Conditional posterior distribution of the latents Y |
fcondYXAcens2 | Conditional posterior distribution of the latents Y in the... |
fcondYZXA | Conditional posterior distribution of the bivariate latents... |
fcondYZXAcens2 | Conditional posterior distribution of the bivariate latents... |
fill_sigmas | Repeat the common scale parameter of a semiparametric model... |
galaxy | Galaxy Data Set |
Galaxy1.out | Fit of MixNRMI1 function to the galaxy dataset |
Galaxy2.out | Fit of MixNRMI2 function to the galaxy dataset |
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... |
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... |
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... |
logf_logu_cond_y | Contribution of the target logdensity of logU to the... |
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... |
MixNRMI2 | Normalized Random Measures Mixture of Type II |
MixNRMI2cens | Normalized Random Measures Mixture of Type II for censored... |
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 |
plotCDF_censored | Plot the Turnbull CDF and fitted CDF for censored data. |
plotCDF_noncensored | Plot the empirical and fitted CDF for non censored data. |
plot_clustering_and_CDF | Plot the clustering and the Cumulative Distribution Function |
plotfit_censored | Plot the density estimate and the 95% credible interval for... |
plotfit_noncensored | Plot the density estimate and the 95% credible interval for... |
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 |
plotPDF_censored | Plot the density for censored data. |
plotPDF_noncensored | Plot the density and a histogram for non censored data. |
plot_prior_number_of_components | This plots the prior distribution on the number of components... |
plot.PY1 | Plot the density estimate and the 95% credible interval |
plot.PY2 | Plot the density estimate and the 95% credible interval |
pp_plot_censored | Plot the percentile-percentile graph for non censored data,... |
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... |
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... |
rfyzstar | Conditional posterior distribution of the distinct vectors... |
rfyzstarcens2 | Conditional posterior distribution of the distinct vectors... |
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 |
salinity | Salinity tolerance |
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 |
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