BNPdensity-package      Bayesian nonparametric density estimation
Enzyme1.out             Fit of MixNRMI1 function to the enzyme dataset
Enzyme2.out             Fit of MixNRMI2 function to the enzyme dataset
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
Galaxy1.out             Fit of MixNRMI1 function to the galaxy dataset
Galaxy2.out             Fit of MixNRMI2 function to the galaxy dataset
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
MvInv                   Invert jump heights function
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.
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.NRMI1               Extract the Conditional Predictive Ordinates
                        (CPOs) from a fitted object
cpo.NRMI2               Extract the Conditional Predictive Ordinates
                        (CPOs) from a fitted object
cpo.multNRMI            Extract the Conditional Predictive Ordinates
                        (CPOs) from a list of fitted objects
dist_name_k_index_converter
                        Convert distribution names to indices
dt_                     Non-standard student-t density
enzyme                  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
give_kernel_name        Gives the kernel name from the integer code
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.
multMixNRMI1            Multiple chains of MixNRMI1
multMixNRMI1cens        Multiple chains of MixNRMI1cens
multMixNRMI2            Multiple chains of MixNRMI2
multMixNRMI2cens        Multiple chains of MixNRMI2cens
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.multNRMI           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.
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.
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
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.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'
print.multNRMI          S3 method for class 'multNRMI'
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.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'
summary.multNRMI        S3 method for class 'multNRMI'
summarytext             Common text for the summary S3 methods
traceplot               Draw a traceplot for multiple chains
