version 0.1.7

DESCRIPTION

@@ -2,7 +2,7 @@ Type: Package
 Package: glmmfields
 Title: Generalized Linear Mixed Models with Robust Random Fields for
         Spatiotemporal Modeling
-Version: 0.1.4
+Version: 0.1.7
 Authors@R: 
     c(person(given = c("Sean", "C."),
              family = "Anderson",
@@ -26,20 +26,23 @@ BugReports: https://github.com/seananderson/glmmfields/issues
 Depends: methods, R (>= 3.4.0), Rcpp (>= 0.12.18)
 Imports: assertthat, broom, broom.mixed, cluster, dplyr (>= 0.8.0),
         forcats, ggplot2 (>= 2.2.0), loo (>= 2.0.0), mvtnorm, nlme,
-        reshape2, rstan (>= 2.18.2), rstantools (>= 1.5.1), tibble
+        RcppParallel (>= 5.0.1), reshape2, rstan (>= 2.18.2),
+        rstantools (>= 2.1.1), tibble
 Suggests: bayesplot, coda, knitr, parallel, rmarkdown, testthat,
         viridis
 LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.8), RcppEigen (>= 0.3.3.3.0),
-        rstan (>= 2.18.2), StanHeaders (>= 2.18.0)
+        RcppParallel (>= 5.0.1), rstan (>= 2.18.2), StanHeaders (>=
+        2.18.0)
 VignetteBuilder: knitr
 Encoding: UTF-8
-RoxygenNote: 7.1.1
+RoxygenNote: 7.2.3
 SystemRequirements: GNU make
 NeedsCompilation: yes
-Packaged: 2020-07-09 04:02:12 UTC; seananderson
+Biarch: true
+Packaged: 2023-03-10 22:07:14 UTC; seananderson
 Author: Sean C. Anderson [aut, cre],
   Eric J. Ward [aut],
   Trustees of Columbia University [cph]
 Maintainer: Sean C. Anderson <sean@seananderson.ca>
 Repository: CRAN
-Date/Publication: 2020-07-09 05:50:03 UTC
+Date/Publication: 2023-03-10 22:50:02 UTC

MD5

@@ -1,53 +1,53 @@
-414ac92c4d39dfe29198ad2334503781 *DESCRIPTION
-616360d02ede2594e93f3106dafe8ade *NAMESPACE
-22e349f0bd517dda5e0ef6b4b97778a4 *NEWS.md
+7efcb6bf4bf941a3d1aedf46febbce78 *DESCRIPTION
+8795f9d3a3f1b84306311a834c03cb77 *NAMESPACE
+0c7eaed6acf539c3e5b9df7c1cbdb71f *NEWS.md
 591501246e19faa6fa46d5db1192581e *R/family.R
-2d8fb55fd1f2692f66040d5f1ffe54bd *R/fitting.R
+67f28947877adabcbe4ff5b5aac74471 *R/fitting.R
 8f87959bc9c0025114d13f40dfe9775f *R/format_data.R
 14808a5ce06013d76df7b23800b55f14 *R/glmmfields-package.R
 2dc03779de722dbb3310a958e45954fe *R/methods.R
 739b7006f78e5bfde7bb3ab137452a28 *R/plot.R
-18958a60f2459df0cb85078849964848 *R/predict.R
+7619bd7a570d76264705782d93b5df95 *R/predict.R
 6d8331b4cc7b91617cc84979adde823f *R/priors.R
 1aaa246c53120c557468a57d12f99a9d *R/sim.R
-db68c0796882372fe8a4a15f76a00567 *R/stan_pars.R
-1c8249eb55b244cf8fa0b573b65d1570 *R/stanmodels.R
-aefbc5c00caad6ec520914cfe1c22bf3 *R/zzz.R
-2f8bb1d2710cde6ce807fc55550b2116 *build/vignette.rds
-88f64e7df66edcf1e4bd7b0abc3412ab *inst/CITATION
-afe22da3c34faa9b829c4b8343ac88c5 *inst/doc/spatial-glms.R
-f01f9b33ec98a387b544845a28fce364 *inst/doc/spatial-glms.Rmd
-2a9a8b64416e0383297de594d22c88fc *inst/doc/spatial-glms.html
-855c064dbf8deaff96c8dc8a87169109 *inst/include/meta_header.hpp
+8e67b680b71478dbbce457b38476233d *R/stan_pars.R
+61a18858d3a3157cf40c7748b37bd828 *R/stanmodels.R
+27ddd17174166eae01f777cbe0add0b4 *build/vignette.rds
+1cc60bdd8610449d30184e0bb374bf46 *configure
+6bea7bdbd44ffa386677bfdec2d1984b *configure.win
+c896d2e11c9aa7c025c3920b3e3eab66 *inst/CITATION
+fef4c8abd269511372a9c0c2d624cff9 *inst/doc/spatial-glms.R
+80c39d81a9aad4f507bae2d075e8d70c *inst/doc/spatial-glms.Rmd
+bcf181f9a48a561e95f473215eb84537 *inst/doc/spatial-glms.html
+855c064dbf8deaff96c8dc8a87169109 *inst/include/stan_meta_header.hpp
+45cf4ce76e5498ffba0c24610f950a8f *inst/stan/glmmfields.stan
+f7045c08b543061ac102cc09b86e4410 *inst/stan/include/license.stan
 9e888023dd26dc4cb904d14bb220b66e *inst/test.R
 5552da1f2ebaa0aa6058b938cdf3a9b4 *man/format_data.Rd
 15120b78c6117c9c85e4b58822d40a6a *man/glmmfields-package.Rd
-b7875aac043cdd89b09ae71dca1b42fb *man/glmmfields.Rd
+683c5d8c9c52976eb0fc5221b422b83a *man/glmmfields.Rd
 a954f93cc60a089aa929d518e48561fc *man/lognormal.Rd
 c68ec5a804539c4cc2a08986cbd6ef26 *man/loo.Rd
 fbcbd8c199641a9ac649d74b87782065 *man/nbinom2.Rd
 0dc17c4537fcae4bc470927a533918d6 *man/plot.glmmfields.Rd
-ce9e0a1ac1151a9d09838e8dc5db68f4 *man/predict.Rd
+d628a28cee511d9f91a1c812ecc125a0 *man/predict.Rd
 fd3ea29fba1004c2c821f73131a3a369 *man/priors.Rd
 267fed93d852a526793e599be97302be *man/sim_glmmfields.Rd
 8b990eb0ba0476def8eadcc3b8d7f284 *man/stan_pars.Rd
 d7466e066fa9fd20977c3dfa70b8bb39 *man/tidy.Rd
-e385b69646bcc4555858feb68eb1f52e *src/Makevars
-2d00973d800c4813504154a0267fe2f8 *src/Makevars.win
-d41d8cd98f00b204e9800998ecf8427e *src/Modules.cpp
-bca3e8755f348f81552bb65fc6001da6 *src/init.cpp
-d41d8cd98f00b204e9800998ecf8427e *src/stan_files/chunks/common_functions.stan
-1343c4c6fedaed31056cbc7c04c44ab7 *src/stan_files/chunks/license.stan
-63ea07fd8aa34d48b4cf4200dd01d67f *src/stan_files/glmmfields.stan
+8eb94ab0ca38362bef9a1ae171d63fad *src/Makevars
+457929755cc1db9abe969d16b0006005 *src/Makevars.win
+a7eb8f56f4dd47984f7e5fbe5fdbefc6 *src/RcppExports.cpp
+426f38a399735d960553185277d67eab *src/stanExports_glmmfields.cc
+752d22017d797bec2d5a8e21e0cabd8d *src/stanExports_glmmfields.h
 962816c110c4a3d50cb8c9729b10f47c *tests/testthat.R
 c9fe58f78c0e1fb163fa157438c24461 *tests/testthat/test-families.R
-96f72035beb3865d574119ce5f26dea6 *tests/testthat/test-fit-ar-processes.R
-15e0d4e2be8f2cefac1f34cd0beee55e *tests/testthat/test-fit-basic.R
-74b578b718b399130f4607057f10a2e4 *tests/testthat/test-fit-observation-models.R
-0f41c6004b6f486a8b2c69200ae883f2 *tests/testthat/test-fit-with-predictors.R
+01f37d955a32c5cbc8c1c310260abac7 *tests/testthat/test-fit-ar-processes.R
+526ad88ece9fb60f761516ce5eea0fb7 *tests/testthat/test-fit-basic.R
+c932386d8a86323560fbf97b4d09a5d2 *tests/testthat/test-fit-observation-models.R
+674eab315a135d0751941b53c86106de *tests/testthat/test-fit-with-predictors.R
 13a1b7fef17c2d9489425f98807cf33d *tests/testthat/test-format-data.R
-a756eae3f79a7b4cf6b4936c21526943 *tests/testthat/test-predict.R
+cd352df2d4e1216390b8219524833f26 *tests/testthat/test-predict.R
 d2a1a8fe460992c766dbd3ba0abfbeaa *tests/testthat/test-priors.R
-c9afa41370ddc60acc527cb96782da2d *tests/testthat/test-stations.R
-34e6b12ba370464b64c80d303f379d7d *tools/make_cc.R
-f01f9b33ec98a387b544845a28fce364 *vignettes/spatial-glms.Rmd
+9605f4d3cf3f1b82de83b7aeb7839aa3 *tests/testthat/test-stations.R
+80c39d81a9aad4f507bae2d075e8d70c *vignettes/spatial-glms.Rmd

NAMESPACE

@@ -22,6 +22,7 @@ export(tidy)
 import(Rcpp)
 import(methods)
 import(rstantools)
+importFrom(RcppParallel,RcppParallelLibs)
 importFrom(assertthat,assert_that)
 importFrom(assertthat,is.count)
 importFrom(assertthat,is.number)
@@ -44,6 +45,7 @@ importFrom(stats,gaussian)
 importFrom(stats,median)
 importFrom(stats,model.frame)
 importFrom(stats,model.matrix)
+importFrom(stats,model.offset)
 importFrom(stats,model.response)
 importFrom(stats,na.omit)
 importFrom(stats,predict)

NEWS.md

@@ -1,3 +1,19 @@
+# glmmfields 0.1.7
+
+* Rebuild with newest rstantools to avoid CRAN NOTE about C++ version
+
+# glmmfields 0.1.6
+
+* Add back RcppParallel as an import
+
+# glmmfields 0.1.5
+
+* Fully delegate installation to rstantools (#15)
+
+* Other minor fixes to pass R CMD check on R devel
+
+* Add offset functionality
+
 # glmmfields 0.1.4
 
 * Make compatible with updated broom.mixed

R/fitting.R

@@ -56,6 +56,9 @@
 #'   lognormal (specified via [lognormal()] as `lognormal(link = "log")`.
 #'   Besides the negative binomial and lognormal, other families are specified
 #'   as shown in \code{\link[stats]{family}}.
+#' @param binomial_N A character object giving the optional name of the column containing
+#'   Binomial sample size. Leave as `NULL` to fit a spatial GLMM with sample sizes (N) = 1,
+#'   equivalent to bernoulli model.
 #' @param covariance The covariance function of the Gaussian Process.
 #'   One of "squared-exponential", "exponential", or "matern".
 #' @param matern_kappa Optional parameter for the Matern covariance function.
@@ -88,6 +91,7 @@
 #' @param cluster The type of clustering algorithm used to determine the knot
 #'   locations. `"pam"` = [cluster::pam()]. The `"kmeans"`
 #'   algorithm will be faster on larger datasets.
+#' @param offset An optional offset vector.
 #' @param ... Any other arguments to pass to [rstan::sampling()].
 #'
 #' @details
@@ -104,9 +108,10 @@
 #' @export
 #' @importFrom rstan sampling vb
 #' @import Rcpp
-#' @importFrom stats dist model.frame model.matrix model.response rnorm runif
+#' @importFrom stats dist model.frame model.matrix model.response rnorm runif model.offset
 #' @importFrom assertthat assert_that is.count is.number
 #' @importFrom stats gaussian na.omit
+#' @importFrom RcppParallel RcppParallelLibs
 #'
 #' @examples
 #' \donttest{
@@ -158,6 +163,7 @@ glmmfields <- function(formula, data, lon, lat,
                        estimate_df = FALSE,
                        estimate_ar = FALSE,
                        family = gaussian(link = "identity"),
+                       binomial_N = NULL,
                        covariance = c("squared-exponential", "exponential", "matern"),
                        matern_kappa = 0.5,
                        algorithm = c("sampling", "meanfield"),
@@ -167,6 +173,7 @@ glmmfields <- function(formula, data, lon, lat,
                        save_log_lik = FALSE,
                        df_lower_bound = 2,
                        cluster = c("pam", "kmeans"),
+                       offset = NULL,
                        ...) {
 
   # argument checks:
@@ -215,11 +222,18 @@ glmmfields <- function(formula, data, lon, lat,
   y <- model.response(mf, "numeric")
   fixed_intercept <- ncol(X) == 0
 
+  if (is.null(offset)) offset <- rep(0, length(y))
+
   if (is.null(time)) {
     data$null_time_ <- 1
     time <- "null_time_"
   }
 
+  if (is.null(binomial_N)) {
+    data$null_N_ <- 1
+    binomial_N <- "null_N_"
+  }
+
   if ("station" %in% names(list(...))) {
     stop(
       "The 'station' argument is no longer needed when calling glmmfields().",
@@ -255,6 +269,7 @@ glmmfields <- function(formula, data, lon, lat,
       prior_rw_sigma = parse_t_prior(prior_rw_sigma),
       prior_beta = parse_t_prior(prior_beta),
       prior_phi = parse_t_prior(prior_phi),
+      offset = offset,
       cov_func = switch(covariance,
         exponential = 0L,
         `squared-exponential` = 1L,
@@ -276,7 +291,8 @@ glmmfields <- function(formula, data, lon, lat,
       matern_kappa = matern_kappa,
       gp_sigma_scaling_factor = gp_sigma_scaling_factor,
       nW = if (fixed_df_value[[1]] > 999 && !estimate_df) 0L else stan_data$nT,
-      df_lower_bound = df_lower_bound
+      df_lower_bound = df_lower_bound,
+      binomialN = data[,binomial_N]
     )
   )
 
@@ -314,6 +330,7 @@ glmmfields <- function(formula, data, lon, lat,
     lon = lon, lat = lat,
     time = time, year_re = year_re,
     station = data_list$stationID, obs_model = obs_model,
+    offset = offset,
     fixed_intercept = fixed_intercept, family = family
   )
   out <- structure(out, class = "glmmfields")

R/predict.R

@@ -15,6 +15,7 @@
 #'   "response" scale (Same as for [stats::predict.glm()]).
 #' @param return_mcmc Logical. Should the full MCMC draws be returned for the
 #'   predictions?
+#' @param offset Optional offset vector to be used in prediction.
 #' @param iter Number of MCMC iterations to draw. Defaults to all.
 #' @param ... Ignored currently
 #'
@@ -68,7 +69,7 @@
 #' )
 #' pred_grid$prediction <- predict(m,
 #'   newdata = pred_grid, type = "response", iter = 100,
-#'   estimate_method = "median"
+#'   estimate_method = "median", offset = rep(0, nrow(pred_grid))
 #' )$estimate
 #'
 #' ggplot(pred_grid, aes(lon, lat, fill = prediction)) +
@@ -127,6 +128,7 @@ predict.glmmfields <- function(object, newdata = NULL,
                                interval = c("confidence", "prediction"),
                                type = c("link", "response"),
                                return_mcmc = FALSE,
+                               offset = NULL,
                                iter = "all", ...) {
   estimate_method <- match.arg(estimate_method)
   interval <- match.arg(interval)
@@ -143,6 +145,12 @@ predict.glmmfields <- function(object, newdata = NULL,
 
   obs_model <- object$obs_model
 
+  if (is.null(newdata)) offset <- object$offset
+  if (is.null(offset) && !is.null(newdata)) offset <- rep(0, nrow(newdata))
+  if (!is.null(newdata) && !is.null(object$offset)) {
+    if (is.null(offset)) stop("Missing `offset` argument.", call. = FALSE)
+  }
+
   # newdata is df with time, y, lon, lat
   # if null, defaults to data used to fit model
   if (is.null(newdata)) newdata <- object$data
@@ -265,6 +273,8 @@ predict.glmmfields <- function(object, newdata = NULL,
   # generate (1) confidence intervals on mean or (2) prediction intervals
   # including obs error
 
+  pred_values <- pred_values + offset
+
   if (type == "response") {
     # gamma or NB2 or poisson:
     if (obs_model %in% c(0, 2, 5, 6)) pred_values <- exp(pred_values)

R/stan_pars.R

@@ -14,11 +14,12 @@ stan_pars <- function(obs_error, estimate_df = TRUE, est_temporalRE = FALSE,
                       estimate_ar = FALSE, fixed_intercept = FALSE,
                       save_log_lik = FALSE) {
   p <- c(
+    #"y_new",
     "gp_sigma",
     "gp_theta",
     "B",
     switch(obs_error[[1]], lognormal = "sigma", gaussian = "sigma",
-      gamma = "CV", nb2 = "nb2_phi"
+      gamma = "CV", nbinom2 = "nb2_phi"
     ),
     "spatialEffectsKnots"
   )

R/stanmodels.R

@@ -1,37 +1,25 @@
-# Part of the bayesdfa package for estimating model parameters
-# Copyright (C) 2015, 2016, 2017 Trustees of Columbia University
-# 
-# This program is free software; you can redistribute it and/or
-# modify it under the terms of the GNU General Public License
-# as published by the Free Software Foundation; either version 3
-# of the License, or (at your option) any later version.
-# 
-# This program is distributed in the hope that it will be useful,
-# but WITHOUT ANY WARRANTY; without even the implied warranty of
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
-# GNU General Public License for more details.
-# 
-# You should have received a copy of the GNU General Public License
-# along with this program; if not, write to the Free Software
-# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301, USA.
+# Generated by rstantools.  Do not edit by hand.
 
-# This file is only intended to be used during the installation process
-# nocov start
-MODELS_HOME <- "src"
-if (!file.exists(MODELS_HOME)) MODELS_HOME <- sub("R$", "src", getwd())
+# names of stan models
+stanmodels <- c("glmmfields")
 
-stan_files <- dir(file.path(MODELS_HOME, "stan_files"),
-                  pattern = "stan$", full.names = TRUE)
-stanmodels <- lapply(stan_files, function(f) {
-  model_cppname <- sub("\\.stan$", "", basename(f))
-  stanfit <- rstan::stanc(f, allow_undefined = TRUE, 
-                          obfuscate_model_name = FALSE)
-  stanfit$model_cpp <- list(model_cppname = stanfit$model_name, 
+# load each stan module
+Rcpp::loadModule("stan_fit4glmmfields_mod", what = TRUE)
+
+# instantiate each stanmodel object
+stanmodels <- sapply(stanmodels, function(model_name) {
+  # create C++ code for stan model
+  stan_file <- if(dir.exists("stan")) "stan" else file.path("inst", "stan")
+  stan_file <- file.path(stan_file, paste0(model_name, ".stan"))
+  stanfit <- rstan::stanc_builder(stan_file,
+                                  allow_undefined = TRUE,
+                                  obfuscate_model_name = FALSE)
+  stanfit$model_cpp <- list(model_cppname = stanfit$model_name,
                             model_cppcode = stanfit$cppcode)
-  return(do.call(methods::new, args = c(stanfit[-(1:3)], Class = "stanmodel", 
-                 mk_cppmodule = function(x) get(paste0("model_", model_cppname)))))
-  }
-)
-names(stanmodels) <- sub("\\.stan$", "", basename(stan_files))
-rm(MODELS_HOME)
-# nocov end
+  # create stanmodel object
+  methods::new(Class = "stanmodel",
+               model_name = stanfit$model_name,
+               model_code = stanfit$model_code,
+               model_cpp = stanfit$model_cpp,
+               mk_cppmodule = function(x) get(paste0("rstantools_model_", model_name)))
+})

configure

@@ -0,0 +1,4 @@
+# Generated by rstantools.  Do not edit by hand.
+
+#! /bin/sh
+"${R_HOME}/bin/Rscript" -e "rstantools::rstan_config()"

configure.win

@@ -0,0 +1,4 @@
+# Generated by rstantools.  Do not edit by hand.
+
+#! /bin/sh
+"${R_HOME}/bin${R_ARCH_BIN}/Rscript.exe" -e "rstantools::rstan_config()"