Estimate the nonhomgogenous poisson process intensity function from grouped data using a normal kernel

nd_nhpp_fixed(distances_col, id_col, data = NULL, mu_0 = 0,
  kappa_0 = 1, nu_0 = 1, sigma_0 = 1, alpha = 1, rho = 1,
  L = 4, K = 4, iter_max, warm_up, thin = 1, seed = NULL)

Arguments

distances_col

name of column in data that contains distances

id_col

name of column in data that contains id grouping variable

data

data.frame object that contains grouped distances

mu_0

mean hyperparameter for mu normal base measure. Default is 0; Normal(0,1).

kappa_0

variance hyperparameter for mu normal base measure. Default is 1; Normal(0,1).

nu_0

df hyperparameter for sigma inv chisq base measure. Default is 1; InvChisq(1,1);

sigma_0

scale hyperparameter for sigma inv chisq base measure. Default is 1; InvChisq(1,1);

alpha

outer DP concentration parameter

rho

inner DP concentration parameter

L

component truncation number

K

intensity cluster truncation number

iter_max

total number of iterations for which to run sampler

warm_up

number of iterations for which to burn-in or "warm-up" sampler

thin

number of iterations to thin by

seed

integer with which to initialize random number generator