| BNPdensity-package | Bayesian nonparametric density estimation |
| 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 inefficiency, silence it. |
| BNPdensity | Bayesian nonparametric density estimation |
| comment_on_NRMI_type | Comment on the NRMI process depending on the value of the parameters |
| 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 fitted objects |
| cpo.NRMI1 | Extract the Conditional Predictive Ordinates (CPOs) from a fitted object |
| cpo.NRMI2 | Extract the Conditional Predictive Ordinates (CPOs) from a fitted object |
| dist_name_k_index_converter | Convert distribution names to indices |
| dt_ | Non-standard student-t density |
| 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 process. |
| expected_number_of_components_stable | Computes the expected number of components for a stable process. |
| fill_sigmas | Repeat the common scale parameter of a semiparametric model to match the dimension of the location parameters. |
| 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. |
| is_censored | Test if the data is censored |
| is_semiparametric | Tests if a fit is a semi parametric or nonparametric model. |
| 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 |
| MvInv | Invert jump heights 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 |
| 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 data |
| plotfit_noncensored | Plot the density estimate and the 95% credible interval for noncensored data |
| plotPDF_censored | Plot the density for censored data. |
| plotPDF_noncensored | Plot the density and a histogram for non censored data. |
| 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 stable process. The Dirichlet process is provided for comparison. |
| pp_plot_censored | Plot the percentile-percentile graph for non censored data, using the Turnbull estimator the position of the percentiles. |
| 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 |
| qq_plot_censored | Plot the quantile-quantile graph for censored data. |
| qq_plot_noncensored | Plot the quantile-quantile graph for non censored data. |
| 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 |
| traceplot | Draw a traceplot for multiple chains |