R/beta_nd_nhpp.R
beta_nd_nhpp.RdEstimate the nonhomgogenous poisson process intensity function from grouped data using a beta base measure
beta_nd_nhpp(distances_col, id_col, data = NULL, mu_sd, tau_sd, L = 4, K = 4, a_0 = 1, b_0 = 1, a_alpha = 1, b_alpha = 1, a_rho = 1, b_rho = 1, iter_max, warm_up, thin = 1, multiple_taus = FALSE, seed = NULL)
| 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_sd | proposal scale for mus |
| tau_sd | proposal scale for mus |
| L | component truncation number |
| K | intensity cluster truncation number |
| a_0 | hyperparameter for mu beta base measure. Default is 1; uniform(0,1). |
| b_0 | hyperparameter for mu beta base measure. Default is 1; uniform(0,1). |
| 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 |
| multiple_taus | logical indicator for whether or not cluster specific scales (tau) should be estimated |
| seed | integer with which to initialize random number generator |