PDMIF package (6,000+ downloads as of 2024) implements the methods relating to various heterogeneous panel data models with interactive effects. Users can implement various heterogeneous panel data models with interactive effects, including linear model, generalized linear model, logistic model, Poisson model, Probit model, quantile model and quantile VAR model. Package also covers heterogeneous panel data models with interactive effects under known group membership structure as well as for clustering where group membership is unknown. Testing slope homogeneity of the models is also included.
Visit Github site for more information: here
For more details: Ando and Fayad (2022) PDMIF: Heterogeneous panel data models with interactive effects in R
Ando, T. (2010) Bayesian Model Selection and Statistical Modeling CRC Press. Here is R code in the book.
Zellner, A. and Ando, T. (2010) A direct Monte Carlo approach for Bayesian analysis of the seemingly unrelated regression model. Journal of Econometrics, 159, 33-45. Here is R code for implementing a direct Monte Carlo.
Ando, T. and Li, K.-C. (2014) A model averaging approach for high-dimensional regression Journal of the American Statistical Association, 505, 254-265. Here is R code for implementing the model averaging procedure.
Ando, T. and Li, K.-C. (2017) A weight-relaxed model averaging approach for high-dimensional generalized linear models. Annals of Statistics, 45, 2654-2679. Here is R code for implementing the averaging procedure.