pred.base {BaPreStoPro} | R Documentation |
Drawing from predictive distribution based on distribution function Fun(x, x0, samples)
or
density dens(x, x0, samples)
.
Samples should contain samples from the posterior distribution of the parameters.
pred.base(samples, Fun, dens, len = 100, x0, method = c("vector", "free"), pred.alg = c("Distribution", "Trajectory"), sampling.alg = c("RejSamp", "InvMethod"), candArea, grid = 0.001)
samples |
MCMC samples |
Fun |
cumulative distribution function |
dens |
density function |
len |
number of samples to be drawn |
x0 |
vector of starting points |
method |
vectorial ("vector") or not ("free") |
pred.alg |
prediction algorithm, "Distribution" or "Trajectory" |
sampling.alg |
sampling algorithm, rejection sampling ("RejSamp") or inversion method ("InvMethod") |
candArea |
candidate area |
grid |
fineness degree |
vector of samples from prediction
Hermann, S. (2016). Bayesian Prediction for Stochastic Processes based on the Euler Approximation Scheme. SFB 823 discussion paper 27/16.