sample.from.prior: Sample from a Prior Gaussian Distribution

In predsci/DICE: DICE: Dynamics of Interacting Community Epidemics

Description

sample.from.prior samples initial guesses for the MCMC procedure using a prior Gaussian distribution for: pC, R0 and the parameters that control the force of infection for the SH and/or SV models

Usage

sample.from.prior(mydata = NULL, model_par = NULL, fit_par = NULL,
  model_pmin = NULL, model_pmax = NULL, fit_pmin = NULL,
  fit_pmax = NULL, model_ymu = NULL, model_sigma = NULL, fit_ymu = NULL,
  fit_sigma = NULL)

Arguments

mydata	A dataframe with all the information for this DICE run
model_par	An array with initial guesses for the parameters for the model region
fit_par	A matrix with initial guesses for the parameters for the fit regions
model_pmin	An array with minimum values for all the model region parameters
model_pmax	An array with maximum values for all the model region parameters
fit_pmin	A matrix with minimum values for all the fit regions parameters
fit_pmax	A matrix with maximum values for all the fit regions parameters
model_ymu	An array with the prior mean values for the model region
model_sigma	An array with the prior standard deviation values for the model region
fit_ymu	A matrix with the prior mean values for the fit regions
fit_sigma	An array with the prior standard deviation values for the model region

Value

An array and matrix of initial parameters for the MCMC procedure

Examples

sample.from.prior(mydata = mydata, model_par = model_par, fit_par = fit_par,
model_pmin = model_pmin, model_pmax = model_pmax, fit_pmin = fit_pmin, fit_pmax = fit_pmax,
model_ymu = model_ymu, model_sigma = model_sigma, fit_ymu = fit_ymu, fit_sigma = fit_sigma)

model 1 (SH): pC, R0, SH
model 2 (SV): pC, R0, SV
model 3 (SH+SV): pC, R0, SH, SV
model 4: pC, R0
model 5: pC, R0

predsci/DICE documentation built on Aug. 9, 2019, 9:41 a.m.