All functions

as.array(<stapDP>)

Retrieve NDP parameter samples in Array Form

as.matrix(<ndp>)

Retrieve Parameter Samples in Matrix Form

assign_mode()

Estimates Posterior Mode Cluster Assignment

base-measure

Base Measures

bend()

Estimate the distribution of (B)uilt (E)nvironment amenities via the (N)ested (D)irichlet Process

bendr-datasets

Datasets for bendr examples

beta_measure()

Beta base measure

beta_nd_nhpp_fit()

Estimate the nonhomgogenous poisson process intensity function from grouped data

bndp()

Create a bndp object

get_square_error()

Calculates Error Distribution under square loss function

green_loss()

Lau and Green posterior loss function

green_loss(<ndp>)

Lau and Green posterior loss function

green_loss_known()

Computes Green and Lau Loss function with known classification

green_loss_unknown()

Computes Green and Lau loss function with unknown classification

groupvo()

Retrieve Grouped Data Structure

nd_nhpp_fit()

Estimate the nonhomgogenous poisson process intensity function from grouped data

nd_nhpp_fixed_fit()

Estimate the nonhomgogenous poisson process intensity function from grouped data with fixed concentration parameters

nsamples(<ndp>)

Methods for ndp objects

ndp()

ndp objects

ndp_fixed()

Create a ndp_fixed object

normal_measure()

Normal Base Measure

plot(<ndp>)

Plot method for ndp objects

plot_cluster_densities()

Plots cluster intensity function densities

plot_global_density()

Plots global density function

plot_pairs()

plots pairwise probability clustering plot

print(<ndp>)

Print method for ndp objects

rnhpp()

Random nonhomogenous poisson process generator

square_error()

Computes Square loss with unknown classification

summary(<ndp>) print(<summary.ndp>)

Summary method for ndp objects

traceplot()

Traceplots of various NDP-NHPP parameters

transform_distances()

Transform Distances