ggdmc (version 0.1.3.9)

rprior: Generate Random Numbers from Prior Probability Distribution

Description

dprior matches 5 types of string: tnorm, beta_lu, gamma_l, lnorm_l, and constant to determine which density functions to call. dprior calls beta, gamma, log-normal density functions via R API. For truncated normal density, dprior calls dtn_scalar, an internal Rcpp function built specific for ggdmc. Whetehr log the probability density is determined by the boolean log sent in via p.prior. This function is akin to DMC's log.prior.dmc.

Usage

rprior(pPrior, n)

Arguments

pPrior

a p.prior list

n

how many random number to generate

Value

a double matrix with nrow equal to the number of random numbers and ncol equal to the number of EAM parameters (npar)

Examples

ddm.prior <- prior.p.dmc(
dists = c("tnorm", "tnorm", "beta", "tnorm", "beta", "beta"),
  p1    = c(a = 1, v = 0, z = 1, sz = 1, sv = 1, t0 = 1),
  p2    = c(a = 1, v = 2, z = 1, sz = 1, sv = 1, t0 = 1),
  lower = c(0,-5, NA, NA, 0, NA),
  upper = c(2, 5, NA, NA, 2, NA))

view(ddm.prior)
##      mean sd lower upper log    dist  untrans
##   a     1  1     0     2   1   tnorm identity
##   v     0  2    -5     5   1   tnorm identity
##   z     1  1     0     1   1 beta_lu identity
##   sz    1  1  -Inf   Inf   1   tnorm identity
##   sv    1  1     0     2   1 beta_lu identity
##   t0    1  1     0     1   1 beta_lu identity

rprior(ddm.prior, 9)
##               a           v         z         sz        sv         t0
## [1,] 0.97413686  0.78446178 0.9975199 -0.5264946 0.5364492 0.55415052
## [2,] 0.72870190  0.97151662 0.8516604  1.6008591 0.3399731 0.96520848
## [3,] 1.63153685  1.96586939 0.9260939  0.7041254 0.4138329 0.78367440
## [4,] 1.55866180  1.43657110 0.6152371  0.1290078 0.2957604 0.23027759
## [5,] 1.32520281 -0.07328408 0.2051155  2.4040387 0.9663111 0.06127237
## [6,] 0.49628528 -0.19374770 0.5142829  2.1452972 0.4335482 0.38410626
## [7,] 0.03655549  0.77223432 0.1739831  1.4431507 0.6257398 0.63228368
## [8,] 0.71197612 -1.15798082 0.8265523  0.3813370 0.4465184 0.23955415
## [9,] 0.38049166  3.32132034 0.9888108  0.9684292 0.8437480 0.13502154