# repYeb: Generate Replicated Data with Estimated Parameters In geoCount: Analysis and Modeling for Geostatistical Count Data

## Description

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

## Usage

 1 2 3 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 β; ignored if "res.m" is given sigma a value which indicates the estimation for σ; ignored if "res.m" is given phi a value which indicates the estimation for φ; ignored if "res.m" is given k a value which indicates the estimation for κ; ignored if "res.m" is given and contains the posterior samples for κ

## Value

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

## Author(s)

Liang Jing ljing918@gmail.com

repYpost, simData.
 1 2 3 4 5 6 7 8 ## 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)