version 2.0.5

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: psbcSpeedUp
 Title: Penalized Semiparametric Bayesian Cox Models
-Version: 2.0.4
-Date: 2023-10-12
+Version: 2.0.5
+Date: 2023-12-08
 URL: https://github.com/ocbe-uio/psbcSpeedUp
 BugReports: https://github.com/ocbe-uio/psbcSpeedUp/issues
 Authors@R: c(person("Zhi", "Zhao", role=c("aut","cre"), email = "zhi.zhao@medisin.uio.no"), 
@@ -13,18 +13,21 @@ License: GPL-3
 Copyright: The C++ files pugixml.cpp, pugixml.h and pugiconfig.h are
         with Copyright (C) 2006-2018 Arseny Kapoulkine and Copyright
         (C) 2003 Kristen Wegner.
+VignetteBuilder: knitr
 Depends: R (>= 4.0)
 Encoding: UTF-8
 RoxygenNote: 7.2.3
 LinkingTo: Rcpp, RcppArmadillo (>= 0.9.000)
-Imports: Rcpp, xml2, ggplot2, GGally, MASS, utils, stats
+Imports: Rcpp, xml2, ggplot2, GGally, MASS, survival, riskRegression,
+        utils, stats
+Suggests: knitr
 LazyData: true
 NeedsCompilation: yes
-Packaged: 2023-10-12 14:26:35 UTC; zhiz
+Packaged: 2023-12-08 13:29:37 UTC; zhiz
 Author: Zhi Zhao [aut, cre],
   Manuela Zucknick [aut],
   Maral Saadati [aut],
   Axel Benner [aut]
 Maintainer: Zhi Zhao <zhi.zhao@medisin.uio.no>
 Repository: CRAN
-Date/Publication: 2023-10-12 14:50:02 UTC
+Date/Publication: 2023-12-08 14:00:02 UTC

MD5

@@ -1,35 +1,44 @@
-1868650e39faca1f5dedc86c07805b25 *DESCRIPTION
-54e2e2200e0daa66e9280c35d1b4000b *NAMESPACE
-ea197f74ec3c62ca7e62a4e0138bd1de *NEWS.md
+2100e91bb0b3d40e8dab72338c31364e *DESCRIPTION
+528177306a09bb4b73a2d277e4774f41 *NAMESPACE
+589656534e41b8049f499f8588b24cb7 *NEWS.md
 7ae1823500df61c6e97cd9c55c9887ee *R/RcppExports.R
-17c06d2717a04d99091398ebdaba248e *R/coef.psbcSpeedUp.R
+e72d4c8e2051f1c3b28f183877177cfa *R/coef.psbcSpeedUp.R
 c0dd2e03b926a0d3c5ee44898121cfbe *R/exampleData.R
-8f6d5a01629e0114c94b6a40b5effb50 *R/plot.psbcSpeedUp.R
-3eaa3a18e170d678eae4987cd3b853de *R/psbcSpeedUp.R
-4942867172878bba53688412bd604ec3 *README.md
-6dbf181478c9ac518bb19a51aabfd071 *cleanup
+705a0e2e69bd51f57ba3946767b27d3e *R/plot.psbcSpeedUp.R
+2d4e430e28f76e8f8ecf4e559f4e27ba *R/plotBrier.R
+ad667492d82cfeb09de126ff0ef00df9 *R/predict.psbcSpeedUp.R
+0f897c98dfb5e258207f57b477748efc *R/psbcSpeedUp.R
+bb43106f8e2b174e93d6b5be3258e87c *README.md
+f5f1417afaaf64682000372990355e1c *build/vignette.rds
+7b46749938e49991ac03f0fec0dd825b *cleanup
 b10b1d4c04f04e9373c3ca9fb70f160f *configure
 b7870d69722ee15726af3d1b9a503c8a *configure.ac
 f91c2ee39ced0e6e91f98b81e9344f11 *data/datalist
 7b548c9bd6a373f888b1abd5f788be24 *data/exampleData.rda
-d5bf793431394a60bbbb8c177199a114 *man/coef.psbcSpeedUp.Rd
+8f9e9b60cc3d91d8587aac05992e1578 *inst/doc/BayesCox.R
+c9b3cf22cbf9c151eff3cd5138214bb3 *inst/doc/BayesCox.Rmd
+c1714fc32357cecdc7b9a25dbd310495 *inst/doc/BayesCox.html
+c71ddfcaa90c21b64cbff740de7f58e1 *man/coef.psbcSpeedUp.Rd
 ceb1aaadfdec68603d5cc77d5f796051 *man/exampleData.Rd
 198b70412d51b344f358c6bdf480f5c7 *man/figures/README_plot_beta.png
-c060bdd050536703a862d7643828f59a *man/plot.psbcSpeedUp.Rd
-ace731c93dee9955cd42e9c1945af37e *man/psbcSpeedUp.Rd
+9d60f8c028133fa5c6a3cd284e1e00ed *man/figures/README_plot_brier.png
+335479598736f774954c56b098dfc737 *man/plot.psbcSpeedUp.Rd
+09fec13c66ae23170a78f21c5cf5b2e9 *man/plotBrier.Rd
+26494214e06876cf942b75ecfde81728 *man/predict.psbcSpeedUp.Rd
+7dc417e48efb39b297c96a458967937f *man/psbcSpeedUp.Rd
 2a825488988b01ee93aea8f884fc9070 *src/Makevars.in
 83488be6b1f2f015234720a0a25ff076 *src/Makevars.win
 4c38a99ae49306c08d6798a2b4c21dbc *src/RcppExports.cpp
-d41d8cd98f00b204e9800998ecf8427e *src/drive-e758d6e6.o.tmp
-488b8a39ebc55e50d4decc286f6b7995 *src/drive.cpp
-15069450d96221dda3b547bae245aaeb *src/drive.h
-ca89b29337087802b658b063fcedf3b1 *src/global.cpp
-fcc63ff239f7e16106ebff3b268e81a8 *src/global.h
-185e7e0d65856fa49943cb9e87e28875 *src/init.c
-6441a235e47e5cf4fde31c3ff81cc10c *src/psbc.cpp
-73b9016725850b3dab1e3bdce00e846d *src/psbc.h
+a208ba9b0b9b6953dd665b516eba303d *src/drive.cpp
+a4d019b89b1606ffd530751c1e640f63 *src/drive.h
+99fa8dc58ea0ffc37d1e6e5e2e51d378 *src/global.cpp
+05ad67a54a213f89504a68cc7a253f86 *src/global.h
+cc174f5cdd978352648cec44c0919628 *src/init.c
+b3fe30bb06c10bed689613b6c0d7c82c *src/psbc.cpp
+ca15a2e754117b535063fb35585ad1ca *src/psbc.h
 63fb7f837f5ead3567c138071d25469d *src/pugiconfig.h
 2a482565cd695663ed7426f6302af0ae *src/pugixml.cpp
 654ec0ae83f4bc6dcdd26c633cb4ee08 *src/pugixml.h
-e07acc941971e653481244878da70084 *src/utils.cpp
-89b7b0a35fd94e7bdec8f425188492eb *src/utils.h
+ed81f47ae1fcab8a9c33b71a53ed8f81 *src/utils.cpp
+ab4382c863ccfbb58cef66a0bb024c33 *src/utils.h
+c9b3cf22cbf9c151eff3cd5138214bb3 *vignettes/BayesCox.Rmd

NAMESPACE

@@ -2,16 +2,28 @@
 
 S3method(coef,psbcSpeedUp)
 S3method(plot,psbcSpeedUp)
+S3method(predict,psbcSpeedUp)
+export(plotBrier)
 export(psbcSpeedUp)
 importFrom(GGally,ggcoef)
 importFrom(MASS,mvrnorm)
 importFrom(Rcpp,evalCpp)
+importFrom(ggplot2,aes)
+importFrom(ggplot2,element_blank)
+importFrom(ggplot2,geom_step)
+importFrom(ggplot2,ggplot)
+importFrom(ggplot2,theme)
 importFrom(ggplot2,xlab)
 importFrom(ggplot2,ylab)
+importFrom(riskRegression,Score)
+importFrom(riskRegression,predictCox)
 importFrom(stats,quantile)
 importFrom(stats,rexp)
 importFrom(stats,rgamma)
 importFrom(stats,runif)
+importFrom(survival,Surv)
+importFrom(survival,coxph)
+importFrom(utils,read.table)
 importFrom(utils,write.table)
 importFrom(xml2,as_xml_document)
 importFrom(xml2,write_xml)

NEWS.md

@@ -4,11 +4,15 @@
 * remove Rcpp::List object, instead writing all output objects into files
 * allow multiple chains and omp for parallelisation
 * add R functions for feature (stability) selection
-* add R functions for survival predictions
 * extend C++ source code for implementing other shrinkage and group priors
 
+# psbcSpeedUp 2.0.5
+
+* Added R functions for survival predictions, e.g. time-dependent Brier scores, integrated Brier score
+
 # psbcSpeedUp 2.0.4
 
+* For Linux machines, installed GitHub v2.0.4 seems twice faster than CRAN v2.0.4 due to `omp_set_*` in drive.cpp to solve CRAN pre-test NOTE `CPU-elapse times ratio`
 * Improved C++ code to speedup 10-20%
 * Declared functions inside PSBC class
 * Added configuration files for checking omp, compilers etc.

R/coef.psbcSpeedUp.R

@@ -24,11 +24,12 @@
 #'
 #' # Set hyperparameters
 #' mypriorPara <- list(
-#'   "groupInd" = 1:p, "eta0" = 0.02, "kappa0" = 1, "c0" = 2, "r" = 10 / 9, 
-#'   "delta" = 1e-05, "lambdaSq" = 1, "sigmaSq" = runif(1, 0.1, 10), 
-#'   "beta.prop.var" = 1, "beta.clin.var" = 1)
+#'   "groupInd" = 1:p, "eta0" = 0.02, "kappa0" = 1, "c0" = 2, "r" = 10 / 9,
+#'   "delta" = 1e-05, "lambdaSq" = 1, "sigmaSq" = runif(1, 0.1, 10),
+#'   "beta.prop.var" = 1, "beta.clin.var" = 1
+#' )
 #'
-#'\donttest{
+#' \donttest{
 #' # run Bayesian Lasso Cox
 #' library("psbcSpeedUp")
 #' set.seed(123)

R/plot.psbcSpeedUp.R

@@ -28,11 +28,12 @@
 #'
 #' # Set hyperparameters
 #' mypriorPara <- list(
-#'   "groupInd" = 1:p, "eta0" = 0.02, "kappa0" = 1, "c0" = 2, "r" = 10 / 9, 
-#'   "delta" = 1e-05, "lambdaSq" = 1, "sigmaSq" = runif(1, 0.1, 10), 
-#'   "beta.prop.var" = 1, "beta.clin.var" = 1)
+#'   "groupInd" = 1:p, "eta0" = 0.02, "kappa0" = 1, "c0" = 2, "r" = 10 / 9,
+#'   "delta" = 1e-05, "lambdaSq" = 1, "sigmaSq" = runif(1, 0.1, 10),
+#'   "beta.prop.var" = 1, "beta.clin.var" = 1
+#' )
 #'
-#'\donttest{
+#' \donttest{
 #' # run Bayesian Lasso Cox
 #' library("psbcSpeedUp")
 #' set.seed(123)
@@ -45,7 +46,7 @@
 #'
 #' @export
 plot.psbcSpeedUp <- function(x, type = "mean", interval = TRUE, ...) {
-  if (!(inherits(x, "psbcSpeedUp") | is.matrix(x))) {
+  if (!(inherits(x, "psbcSpeedUp") || is.matrix(x))) {
     stop("Use only with 'psbcSpeedUp' object or a matrix!")
   }
 
@@ -63,14 +64,14 @@ plot.psbcSpeedUp <- function(x, type = "mean", interval = TRUE, ...) {
 
   if (inherits(x, "psbcSpeedUp")) {
     if (is.null(colnames(x$output$beta.p))) {
-      x_names <- paste0("x", 1:ncol(x$output$beta.p))
+      x_names <- paste0("x", seq_len(ncol(x$output$beta.p)))
     } else {
       x_names <- colnames(x$output$beta.p)
     }
     beta_p <- x$output$beta.p[-(1:(x$input$burnin / x$input$thin + 1)), ]
   } else {
     if (is.null(colnames(x))) {
-      x_names <- paste0("x", 1:ncol(x))
+      x_names <- paste0("x", seq_len(ncol(x)))
     } else {
       x_names <- colnames(x)
     }

R/plotBrier.R

@@ -0,0 +1,64 @@
+#' psbcSpeedUp
+#'
+#' @title Time-dependent Brier scores
+#'
+#' @description
+#' Predict time-dependent Brier scores based on Cox regression models
+#'
+#' @name plotBrier
+#' 
+#' @importFrom ggplot2 ggplot aes geom_step theme element_blank
+#' 
+#' @param object fitted object obtained with \code{psbcSpeedUp}
+#' @param survObj.new a list containing observed data from new subjects with
+#' components \code{t}, \code{di}, \code{x}. If \code{NULL}, the prediction is
+#' based on the training data
+#' @param times maximum time point to evaluate the prediction
+#' @param method option to use the posterior mean (\code{"mean"}) of coefficients
+#' for prediction or Bayesian model averaging (\code{"BMA"}) for prediction
+#' @param \dots not used
+#'
+#' @keywords survival
+##' @examples
+##'
+#' # Load the example dataset
+#' data("exampleData", package = "psbcSpeedUp")
+#' p <- exampleData$p
+#' q <- exampleData$q
+#' survObj <- exampleData[1:3]
+#'
+#' # Set hyperparameters
+#' mypriorPara <- list(
+#'   "groupInd" = 1:p, "eta0" = 0.02, "kappa0" = 1, "c0" = 2, "r" = 10 / 9,
+#'   "delta" = 1e-05, "lambdaSq" = 1, "sigmaSq" = runif(1, 0.1, 10),
+#'   "beta.prop.var" = 1, "beta.clin.var" = 1)
+#'
+#' \donttest{
+#' # run Bayesian Lasso Cox
+#' library("psbcSpeedUp")
+#' set.seed(123)
+#' fitBayesCox <- psbcSpeedUp(survObj,
+#'   p = p, q = q, hyperpar = mypriorPara,
+#'   nIter = 10, burnin = 0, outFilePath = tempdir()
+#' )
+#' # predict survival probabilities of the train data
+#' plotBrier(fitBayesCox, times = 80)
+#' }
+#'
+#' @export
+plotBrier <- function(object, survObj.new = NULL, 
+                      method = "mean", times = NULL, ...) {
+
+  Brier_score <- predict.psbcSpeedUp(object, 
+                                      survObj.new = survObj.new, 
+                                      method = method, 
+                                      times = times)
+  Brier <- model <- NULL
+  #Brier_score %>%
+    ggplot2::ggplot(Brier_score, 
+                    aes(times, Brier, group = model, color = model)) +
+    xlab("Evaluation time points") +
+    ylab("Brier score") +
+    geom_step(direction = "vh") +
+    theme(legend.title = element_blank())
+}