Estimate the nonhomgogenous poisson process intensity function from grouped data using multiple taus

beta_nd_nhpp_fit_multiple_taus(r, n_j, d, mu_sd, tau_sd, L, K, J, a_0, b_0,
  a_alpha, b_alpha, a_rho, b_rho, iter_max, warm_up, thin, seed, chain)

Arguments

r

vector of distances associatd with different BEFs

n_j

matrix of integers denoting the start and length of each school's associated BEF distances

d

a 1D grid of positive real values over which the differing intensities are evaluated

mu_sd

scale for mu proposal dist'n

tau_sd

not used

L

component truncation number

K

intensity cluster truncation number

J

number of rows in r matrix; number of groups

a_0

hyperparameter for mu base measure

b_0

hyperparameter for mu base measure

a_alpha

hyperparameter for alpha gamma prior

b_alpha

hyperparameter for alpha gamma prior

a_rho

hyperparameter for rho gamma prior

b_rho

hyperparameter for rho gamma prior

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

chain

integer chain label