View source: R/pmpp_aux_funcs.R
Produce negative log-likelihood in the GMM case
1 2 | loglikelihood_GMM(theta, rho_GMMpar, alpha_GMMpar, sigma2_GMMpar, n_alpha,
X_mat, Y_mat, Z_mat, W, T, N, aux_Y0)
|
theta |
vector of homogeneous parameters |
rho_GMMpar |
lagged dependent variables coefficient estimates from the GMM |
alpha_GMMpar |
external variables coefficient estimates from the GMM |
sigma2_GMMpar |
variance of the shocks estimated using GMM residuals |
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 |
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