pred.base: Bayesian prediction function

Description Usage Arguments Value References

View source: R/predict.R

Description

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.

Usage

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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)

Arguments

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

Value

vector of samples from prediction

References

Hermann, S. (2016). Bayesian Prediction for Stochastic Processes based on the Euler Approximation Scheme. SFB 823 discussion paper 27/16.


SimoneHermann/BaPreStoPro documentation built on May 10, 2017, 1:42 p.m.