Rapid and Accurate Genetic Prediction Modeling for Genome-Wide Association or Whole-Genome Sequencing Study Data R package stmgp version 1.0.4.2 Rapidly build accurate genetic prediction models for genome-wide association or whole-genome sequencing study data by smooth-threshold multivariate genetic prediction (STMGP) method. Variable selection is performed using marginal association test p-values with an optimal p-value cutoff selected by Cp-type criterion. Quantitative and binary traits are modeled respectively via linear and logistic regression models. A function that works through PLINK software (Purcell et al. 2007 <DOI:10.1086/519795>, Chang et al. 2015 <DOI:10.1186/s13742-015-0047-8>) <https://www.cog-genomics.org/plink2> is provided. Covariates can be included in regression model. Software Depends: MASS Masao Ueki <uekimrsd@nifty.com> Comprehensive R Archive Network (CRAN) Masao Ueki [aut, cre] GPL (>= 2) 2025-10-03 application/tgz https://CRAN.R-project.org/package=stmgp doi:10.32614/CRAN.package.stmgp