An R package for regression analysis of data from extreme sampling
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Updated
May 3, 2022 - R
An R package for regression analysis of data from extreme sampling
Random Forest Two Sample Testing
R package for Non-local Prior Based Iterative Variable Selection for Genome-Wide Association Studies, or Other High-Dimensional Data
Implementation MWPCR with R
R Package: Adaptively weighted group lasso for semiparametic quantile regression models
Statistical inference in sparse high-dimensional additive models
Biomarker selection in penalized regression models
R codes and dataset for the estimation of the high-dimensional state space model proposed in the paper "A dynamic factor model approach to incorporate Big Data in state space models for official statistics" with Franz Palm, Stephan Smeekes and Jan van den Brakel.
Replicate the results of nowcasting housing sales by Google Queries, using Bayesian Structural Time-Series Model (Choi & Varian, 2009, 2012).
Implementation of the FNETS methodology proposed in Barigozzi, Cho and Owens (2024) for network estimation and forecasting of high-dimensional time series
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