GMM_parametric: Produce posterior means of lambda's for the parametric GMM...

Description Usage Arguments

View source: R/pmpp_aux_funcs.R

Description

Produce posterior means of lambda's for the parametric GMM implementation given autoregressive coefficient (rho)

Usage

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GMM_parametric(rho, alpha = 0, optim_method, init, n_lambda, n_alpha,
  X_mat, Y_mat, Z_mat, W, T, N, aux_Y0, common_par_method, X_star, Y_star,
  Z_star)

Arguments

rho

lagged dependent variable coefficients

alpha

external variables coefficients

optim_method

optimization method

init

initial values for the optimization routine

n_lambda

number of columns in W; currently always set to 1

n_alpha

number of external variables

X_mat

lagged dependent variable matrix

Y_mat

dependent variable matrix

Z_mat

external variable matrix

W

cross-sectionally invariant variables - not used now

T

time dimension of the data

N

cross-sectional dimension of the data

aux_Y0

auxiliary matrix with initial observations of the dependent variable

common_par_method

method for estimating common parameters

X_star

auxiliary matrix for OFD transformation

Y_star

auxiliary matrix for OFD transformation

Z_star

auxiliary matrix for OFD transformation


pmpp documentation built on Oct. 30, 2019, 11:35 a.m.