bayesetel {betel}R Documentation

bayesetel MCMC estimation of moment condition models by the Chib, Shin and Simoni (2018) method

Description

bayesetel MCMC estimation of moment condition models by the Chib, Shin and Simoni (2018) method

Usage

bayesetel(
  gfunc = gfunc,
  y = y,
  dat = dat,
  psi0 = psi0,
  lam0 = lam0,
  psi0_ = psi0_,
  Psi0_ = Psi0_,
  nu = 2.5,
  nuprop = 15,
  controlpsi = list(maxiterpsi = 1000, mingrpsi = 1e-08),
  controllam = list(maxiterlam = 50, mingrlam = 1e-07),
  maxiterlammcmc = 50,
  numloops = 75,
  probnb = 0.35,
  printstep = 2000,
  n0 = 1000,
  m = 10000,
  seed = 100
)

Arguments

gfunc

is the list of moment functions

y
dat
psi0

is the starting value of psi = (theta,v)

lam0

is the starting value of lambda

psi0_

is the prior mean of psi

Psi0_

is the vector of prior dispersions of psi

nu

is the df of the prior student-t

nuprop

is the df of the student-t proposal

controlpsi

is a list of parameters in maximizing likelihood over psi

controllam

is a list of parameters in minimizing dual over lambda

maxiterlammcmc

is the maxiter for the dual in the MCMC iterations

numloops
probnb
printstep

is the interval between prints to the screen

n0

burn-in

m

iterations beyond burn-in

seed

is the seed

Author(s)

Siddhartha Chib


[Package betel version 1.0 Index]