| create_fframe | Add empty rows with time stamps to each cress-sectional unit in the panel |
| get_kernel | Obtain 2D kernel density estimates given sufficient statistics for lambdas and the initial data Y0 |
| get_lambda0 | Produce sufficient statistics (lambda0) given the common coefficients (rho0) |
| get_sigma2 | Produce variance of the shocks estimated using GMM residues (sigma2_0) given the common coefficients (rho0) |
| GMM_parametric | Produce posterior means of lambda's for the parametric GMM implementation given autoregressive coefficient (rho) |
| kde | One-dimensional kernel density estimate |
| kde2D | Compute a two-dimensional kernel density estimate |
| loglikelihood_GMM | Produce negative log-likelihood in the GMM case |
| loglikelihood_QMLE | Produce (negative) log marginal likelihood for QMLE with correlated random coefficients |
| plot.pmpp | Plot method for objects of class 'pmpp'. |
| pmpp | Posterior Mean Panel Predictor for dynamic panel modelling |
| pmpp_data | Transform a single variable in the matrix format into the long panel format |
| pmpp_predinterval | Random-Window Block Bootstrap for prediction intervals for PMPP model |
| post_mean_lambda_par | Provide posterior means of lambda_i's based on the Parametric Posterior Mean estimator with correlated random coefficients |
| predict.pmpp | Compute forecasts with a PMPP model |
| ssys_gmm | Suboptimal multi-step System-GMM estimator for AR(1) panel data model |
| summary.pmpp | Summary method for objects of class 'pmpp'. |