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R/GxESelection.R

@@ -11,7 +11,7 @@
 #'
 #' @references
 #' Ren, J., Zhou, F., Li, X., Ma, S., Jiang, Y. and Wu, C. (2023) Robust Bayesian variable selection for
-#' gene-environment interactions. \emph{Biometrics}, 79(2):684-694. doi: \url{https://doi.org/10.1111/biom.13670}. PMID: 35394058.
+#' gene-environment interactions. \emph{Biometrics}, 79(2):684-694. \doi{10.1111/biom.13670}. PMID: 35394058.
 #'
 #' Barbieri, M.M. and Berger, J.O. (2004). Optimal predictive model selection. {\emph{Ann. Statist}, 32(3):870–897}
 #'

R/roben-package.R

@@ -25,35 +25,35 @@ NULL
 #' predict() takes a roben object and returns the predicted values for new observations.
 #'
 #' @references
-#' Ren, J., Zhou, F., Li, X., Ma, S., Jiang, Y. and Wu, C. (2023) Robust Bayesian variable selection for
-#' gene-environment interactions. \emph{Biometrics}, 79(2):684-694. doi: \url{https://doi.org/10.1111/biom.13670}. PMID: 35394058.
+#' Ren, J., Zhou, F., Li, X., Ma, S., Jiang, Y., and Wu, C. (2023). Robust Bayesian variable selection for gene-environment interactions.
+#' \emph{Biometrics}, 79(2):684-694. \doi{10.1111/biom.13670}. PMID: 35394058.
 #'
-#' Wu, C. and Ma, S. (2015). A selective review of robust variable selection with applications in bioinformatics.
-#' {\emph{Briefings in Bioinformatics}, 16(5), 873–883} \url{https://doi.org/10.1093/bib/bbu046}
+#' Wu, C., and Ma, S. (2015). A selective review of robust variable selection with applications in bioinformatics.
+#' \emph{Briefings in Bioinformatics}, 16(5), 873–883. \doi{10.1093/bib/bbu046}.
 #'
-#' Zhou, F., Ren, J., Lu, X., Ma, S. and Wu, C. (2021). Gene-Environment Interaction: A Variable Selection Perspective.
-#' \emph{Methods in Molecular Biology}, 2212:191-223. doi: \url{https://doi.org/10.1007/978-1-0716-0947-7_13}. PMID: 33733358.
+#' Zhou, F., Ren, J., Lu, X., Ma, S., and Wu, C. (2021). Gene-Environment Interaction: A Variable Selection Perspective.
+#' \emph{Methods in Molecular Biology}, 2212:191-223. \doi{10.1007/978-1-0716-0947-7_13}. PMID: 33733358.
 #'
-#' Ren, J., Zhou, F., Li, X., Chen, Q., Zhang, H., Ma, S., Jiang, Y. and Wu, C. (2020) Semi-parametric Bayesian variable selection for gene-environment interactions.
-#' {\emph{Statistics in Medicine}, 39: 617– 638} \url{https://doi.org/10.1002/sim.8434}
+#' Ren, J., Zhou, F., Li, X., Chen, Q., Zhang, H., Ma, S., Jiang, Y., and Wu, C. (2020). Semi-parametric Bayesian variable selection for
+#' gene-environment interactions. \emph{Statistics in Medicine}, 39: 617–638. \doi{10.1002/sim.8434}.
 #'
-#' Ren, J., Zhou, F., Li, X., Wu, C. and Jiang, Y. (2019) spinBayes: Semi-Parametric Gene-Environment Interaction via Bayesian Variable Selection.
-#' R package version 0.1.0. \url{https://CRAN.R-project.org/package=spinBayes}
+#' Ren, J., Zhou, F., Li, X., Wu, C., and Jiang, Y. (2019). spinBayes: Semi-Parametric Gene-Environment Interaction via
+#' Bayesian Variable Selection. R package version 0.1.0. \url{https://CRAN.R-project.org/package=spinBayes}.
 #'
-#' Wu, C., Jiang, Y., Ren, J., Cui, Y. and Ma, S. (2018). Dissecting gene-environment interactions: A penalized robust approach accounting for hierarchical structures.
-#' {\emph{Statistics in Medicine}, 37:437–456} \url{https://doi.org/10.1002/sim.7518}
+#' Wu, C., Jiang, Y., Ren, J., Cui, Y., and Ma, S. (2018). Dissecting gene-environment interactions: A penalized robust approach
+#' accounting for hierarchical structures. \emph{Statistics in Medicine}, 37:437–456. \doi{10.1002/sim.7518}.
 #'
-#' Wu, C., Shi, X., Cui, Y. and Ma, S. (2015). A penalized robust semiparametric approach for gene-environment interactions.
-#' {\emph{Statistics in Medicine}, 34 (30): 4016–4030} \url{https://doi.org/10.1002/sim.6609}
+#' Wu, C., Shi, X., Cui, Y., and Ma, S. (2015). A penalized robust semiparametric approach for gene-environment interactions.
+#' \emph{Statistics in Medicine}, 34(30): 4016–4030. \doi{10.1002/sim.6609}.
 #'
-#' Wu, C., Cui, Y., and Ma, S. (2014). Integrative analysis of gene–environment interactions under a multi–response partially linear varying coefficient model.
-#' {\emph{Statistics in Medicine}, 33(28), 4988–4998} \url{https://doi.org/10.1002/sim.6287}
+#' Wu, C., Cui, Y., and Ma, S. (2014). Integrative analysis of gene–environment interactions under a multi–response partially linear
+#' varying coefficient model. \emph{Statistics in Medicine}, 33(28): 4988–4998. \doi{10.1002/sim.6287}.
 #'
-#' Wu, C., Zhong, P.S. and Cui, Y. (2018). Additive varying–coefficient model for nonlinear gene–environment interactions.
-#' {\emph{Statistical Applications in Genetics and Molecular Biology}, 17(2)} \url{https://doi.org/10.1515/sagmb-2017-0008}
+#' Wu, C., Zhong, P.S., and Cui, Y. (2018). Additive varying–coefficient model for nonlinear gene–environment interactions.
+#' \emph{Statistical Applications in Genetics and Molecular Biology}, 17(2). \doi{10.1515/sagmb-2017-0008}.
 #'
-#' Wu, C., Zhong, P.S. and Cui, Y. (2013). High dimensional variable selection for gene-environment interactions.
-#' {\emph{Technical Report. Michigan State University.}}
+#' Wu, C., Zhong, P.S., and Cui, Y. (2013). High dimensional variable selection for gene-environment interactions.
+#' \emph{Technical Report. Michigan State University.}
 #'
 #' @seealso \code{\link{roben}}
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