geoCount (version 1.150120)

repYeb: Generate Replicated Data with Estimated Parameters

Description

This function generates replicated data sets based on estimated parameters (given or from posterior samples).

Usage

repYeb(N.sim, loc, L, X = NULL, rho.family = "rhoPowerExp",  Y.family="Poisson", res.m = NULL, est = "mode",  beta = NULL, sigma = NULL, phi = NULL, k = 1)

Arguments

N.sim

the number of replicated data sets to be simulated

loc

a $n \times 2$ matrix which indicates the coordinates of observed locations

L

a vector of length n; it indicates the time duration during which the Poisson counts are accumulated, or the total number of trials for Binomial response

X

a $n \times p$ covariate matrix; the default value "NULL" indicates no covariate

rho.family

take the value of "rhoPowerExp" or "rhoMatern" which indicates the powered exponential or Matern correlation function is used

Y.family

take the value of "Poisson" or "Binomial" which indicates Poisson or Binomial distribution for response variables

res.m

a list with elements containing the posterior samples of latent variables and parameters for observed locations

est

take the value of "mode" which indicates the mode of posterior samples will be used as the parameter estimate; otherwise, the mean will be used

beta

a value which indicates the estimation for $\beta$; ignored if "res.m" is given

sigma

a value which indicates the estimation for $\sigma$; ignored if "res.m" is given

phi

a value which indicates the estimation for $\phi$; ignored if "res.m" is given

k

a value which indicates the estimation for $\kappa$; ignored if "res.m" is given and contains the posterior samples for $\kappa$

Value

A $n \times N.sim$ matrix of replicated data sets.

See Also

repYpost, simData.

Examples

## Not run: 
# # Estimate parameters from posterior samples
# Yrep.eb <- repYeb(N.sim=2000, loc, L, res.m, est = "mode")
# # Pre-determined parameters (also an efficient way to simulate massive data sets)
# Yrep.eb <- repYeb(N.sim=2000, loc, L, beta = 5, sigma = 1, phi = 0.1, 
#                   k = 1)
# ## End(Not run)