revert to static Makevars.win + add hatvalues()

.github/workflows/R-CMD-check.yaml

@@ -39,7 +39,6 @@ jobs:
           - {os: windows-latest, r: 'devel', rtools: '44'}
           - {os: windows-latest, r: 'next', rtools: '44'}
           - {os: windows-latest, r: 'release', rtools: '43'}
-          #- {os: windows-latest, r: 'oldrel', rtools: '42'}
           - {os: ubuntu-latest, r: 'devel'}
           - {os: ubuntu-latest, r: 'next'}
           - {os: ubuntu-latest, r: 'release'}
@@ -48,9 +47,6 @@ jobs:
     env:
       GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
       R_KEEP_PKG_SOURCE: yes
-      RTOOLS42_HOME: C:\rtools42
-      RTOOLS43_HOME: C:\rtools43
-      RTOOLS44_HOME: C:\rtools44
 
     steps:
       - name: Configure git
@@ -72,13 +68,6 @@ jobs:
         run: |
           brew install gsl
 
-      - name: Install gsl (windows)
-        if: runner.os == 'windows'
-        run: |
-          pacman -Sy --noconfirm
-          pacman -S --noconfirm mingw-w64-{i686,x86_64}-gsl
-        shell: bash
-
       - uses: r-lib/actions/setup-r-dependencies@v2
         with:
           extra-packages: rcmdcheck

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: gslnls
 Type: Package
 Title: GSL Multi-Start Nonlinear Least-Squares Fitting
-Version: 1.3.1
-Date: 2024-04-25
+Version: 1.3.2
+Date: 2024-04-30
 Authors@R: person("Joris", "Chau", email = "[email protected]", role = c("aut", "cre"))
 Description: An R interface to nonlinear least-squares optimization with the GNU Scientific Library (GSL), see M. Galassi et al. (2009, ISBN:0954612078). The available trust region methods include the Levenberg-Marquardt algorithm with and without geodesic acceleration, the Steihaug-Toint conjugate gradient algorithm for large systems and several variants of Powell's dogleg algorithm. Multi-start optimization based on quasi-random samples is implemented using a modified version of the algorithm in Hickernell and Yuan (1997, OR Transactions). Bindings are provided to tune a number of parameters affecting the low-level aspects of the trust region algorithms. The interface mimics R's nls() function and returns model objects inheriting from the same class.
 BugReports: https://github.com/JorisChau/gslnls/issues

NAMESPACE

@@ -12,6 +12,7 @@ S3method(gsl_nls,"function")
 S3method(gsl_nls,formula)
 S3method(gsl_nls_large,"function")
 S3method(gsl_nls_large,formula)
+S3method(hatvalues,gsl_nls)
 S3method(logLik,gsl_nls)
 S3method(nobs,gsl_nls)
 S3method(predict,gsl_nls)
@@ -35,6 +36,7 @@ importFrom(stats,df.residual)
 importFrom(stats,fitted)
 importFrom(stats,formula)
 importFrom(stats,getInitial)
+importFrom(stats,hatvalues)
 importFrom(stats,model.weights)
 importFrom(stats,nls)
 importFrom(stats,nls.control)

NEWS.md

@@ -1,3 +1,8 @@
+# gslnls 1.3.2
+
+* Reverted to static Makevars.win (supplied by T. Kalibera)
+* Added new method `hatvalues()`
+
 # gslnls 1.3.1
 
 * Minor edits configure.ac to fix cran check results

R/nls.R

@@ -108,7 +108,8 @@
 #' See the individual method descriptions for the structures of the returned lists and the generic functions
 #' applicable to objects of both classes.
 #' @useDynLib gslnls, .registration = TRUE
-#' @importFrom stats nls numericDeriv deriv as.formula coef deviance df.residual fitted vcov formula getInitial model.weights pf pt qt setNames sigma nobs
+#' @importFrom stats nls numericDeriv deriv as.formula coef deviance df.residual fitted vcov formula getInitial model.weights
+#' @importFrom stats pf pt qt setNames sigma nobs hatvalues
 #' @seealso \code{\link[stats]{nls}}
 #' @seealso \url{https://www.gnu.org/software/gsl/doc/html/nls.html}
 #' @references M. Galassi et al., \emph{GNU Scientific Library Reference Manual (3rd Ed.)}, ISBN 0954612078.

R/nls_methods.R

@@ -425,6 +425,32 @@ vcov.gsl_nls <- function(object, ...) {
   sm$cov.unscaled * sm$sigma^2
 }
 
+#' Calculate leverage values
+#' @description Returns leverage values (hat values) from a fitted \code{"gsl_nls"} object based on the estimated
+#' variance-covariance matrix of the model parameters.
+#' @inheritParams coef.gsl_nls
+#' @param model An object inheriting from class \code{"gsl_nls"}.
+#' @return Numeric vector of leverage values similar to \code{\link[stats]{hatvalues}}.
+#' @seealso \code{\link[stats]{hatvalues}}
+#' @examples
+#' ## data
+#' set.seed(1)
+#' n <- 25
+#' xy <- data.frame(
+#'  x = (1:n) / n,
+#'  y = 2.5 * exp(-1.5 * (1:n) / n) + rnorm(n, sd = 0.1)
+#' )
+#' ## model
+#' obj <- gsl_nls(fn = y ~ A * exp(-lam * x), data = xy, start = c(A = 1, lam = 1))
+#'
+#' hatvalues(obj)
+#' @export
+hatvalues.gsl_nls <- function(model, ...) {
+  J <- model$m$gradient()
+  JtJinv <- chol2inv(model$m$Rmat())
+  diag((J %*% JtJinv) %*% t(J))
+}
+
 #' Anova tables
 #' @description Returns the analysis of variance (or deviance) tables for two or
 #' more fitted \code{"gsl_nls"} objects.

configure

@@ -1,6 +1,6 @@
 #! /bin/sh
 # Guess values for system-dependent variables and create Makefiles.
-# Generated by GNU Autoconf 2.71 for gslnls 1.3.1.
+# Generated by GNU Autoconf 2.71 for gslnls 1.3.2.
 #
 # Report bugs to <https://github.com/JorisChau/gslnls/issues/>.
 #
@@ -610,8 +610,8 @@ MAKEFLAGS=
 # Identity of this package.
 PACKAGE_NAME='gslnls'
 PACKAGE_TARNAME='gslnls'
-PACKAGE_VERSION='1.3.1'
-PACKAGE_STRING='gslnls 1.3.1'
+PACKAGE_VERSION='1.3.2'
+PACKAGE_STRING='gslnls 1.3.2'
 PACKAGE_BUGREPORT='https://github.com/JorisChau/gslnls/issues/'
 PACKAGE_URL=''
 
@@ -1231,7 +1231,7 @@ if test "$ac_init_help" = "long"; then
   # Omit some internal or obsolete options to make the list less imposing.
   # This message is too long to be a string in the A/UX 3.1 sh.
   cat <<_ACEOF
-\`configure' configures gslnls 1.3.1 to adapt to many kinds of systems.
+\`configure' configures gslnls 1.3.2 to adapt to many kinds of systems.
 
 Usage: $0 [OPTION]... [VAR=VALUE]...
 
@@ -1293,7 +1293,7 @@ fi
 
 if test -n "$ac_init_help"; then
   case $ac_init_help in
-     short | recursive ) echo "Configuration of gslnls 1.3.1:";;
+     short | recursive ) echo "Configuration of gslnls 1.3.2:";;
    esac
   cat <<\_ACEOF
 
@@ -1375,7 +1375,7 @@ fi
 test -n "$ac_init_help" && exit $ac_status
 if $ac_init_version; then
   cat <<\_ACEOF
-gslnls configure 1.3.1
+gslnls configure 1.3.2
 generated by GNU Autoconf 2.71
 
 Copyright (C) 2021 Free Software Foundation, Inc.
@@ -1533,7 +1533,7 @@ cat >config.log <<_ACEOF
 This file contains any messages produced by compilers while
 running configure, to aid debugging if configure makes a mistake.
 
-It was created by gslnls $as_me 1.3.1, which was
+It was created by gslnls $as_me 1.3.2, which was
 generated by GNU Autoconf 2.71.  Invocation command line was
 
   $ $0$ac_configure_args_raw
@@ -4066,7 +4066,7 @@ cat >>$CONFIG_STATUS <<\_ACEOF || ac_write_fail=1
 # report actual input values of CONFIG_FILES etc. instead of their
 # values after options handling.
 ac_log="
-This file was extended by gslnls $as_me 1.3.1, which was
+This file was extended by gslnls $as_me 1.3.2, which was
 generated by GNU Autoconf 2.71.  Invocation command line was
 
   CONFIG_FILES    = $CONFIG_FILES
@@ -4121,7 +4121,7 @@ ac_cs_config_escaped=`printf "%s\n" "$ac_cs_config" | sed "s/^ //; s/'/'\\\\\\\\
 cat >>$CONFIG_STATUS <<_ACEOF || ac_write_fail=1
 ac_cs_config='$ac_cs_config_escaped'
 ac_cs_version="\\
-gslnls config.status 1.3.1
+gslnls config.status 1.3.2
 configured by $0, generated by GNU Autoconf 2.71,
   with options \\"\$ac_cs_config\\"
 

configure.ac

@@ -1,5 +1,5 @@
 
-AC_INIT([gslnls],[1.3.1],[https://github.com/JorisChau/gslnls/issues/])
+AC_INIT([gslnls],[1.3.2],[https://github.com/JorisChau/gslnls/issues/])
 
 : ${R_HOME=`R RHOME`}
 if test -z "${R_HOME}"; then

cran-comments.md

@@ -1,10 +1,11 @@
-## CRAN package version 1.3.1
+## CRAN package version 1.3.2
 
 * System requirements: GSL (>= 2.2)
 
 ## Comments
 
-* Edited configure.ac + configure to fix cran check errors (fedora builds)
+* Removed configure.win + Makevars.win.in 
+* Added static Makevars.win as recommended by T. Kalibera
 
 ## Test environments
 

inst/unit_tests/unit_tests_gslnls.R

@@ -237,13 +237,13 @@ penalty_fit_dgT <- gsl_nls_large(
   fn = function(theta) c(sqrt(1e-5) * (theta - 1), sum(theta^2) - 0.25),
   y = rep(0, 11L),
   start = rep(0.15, 10L),
-  jac = function(theta) as(rbind(diag(rep(sqrt(1e-5), length(theta))), 2 * t(theta)), Class = "dgTMatrix")
+  jac = function(theta) as(rbind(diag(rep(sqrt(1e-5), length(theta))), 2 * t(theta)), Class = "TsparseMatrix")
 )
 penalty_fit_dge <- gsl_nls_large(
   fn = function(theta) c(sqrt(1e-5) * (theta - 1), sum(theta^2) - 0.25),
   y = rep(0, 11L),
   start = rep(0.15, 10L),
-  jac = function(theta) as(rbind(diag(rep(sqrt(1e-5), length(theta))), 2 * t(theta)), Class = "dgeMatrix")
+  jac = function(theta) as(rbind(diag(rep(sqrt(1e-5), length(theta))), 2 * t(theta)), Class = "unpackedMatrix")
 )
 
 dotest_tol("1.8.6", inherits(penalty_fit_dgC, "gsl_nls"), TRUE)
@@ -272,6 +272,7 @@ if(requireNamespace("MASS")) {
 }
 dotest("1.9.14", dim(confintd(misra1a_fit1, expr = "b1 + b2")), c(1L, 3L))
 dotest("1.9.15", capture.output(misra1a_fit1)[c(1, 2)], c("Nonlinear regression model", "  model: y ~ b1 * (1 - exp(-b2 * x))"))
+dotest("1.9.16", length(hatvalues(misra1a_fit1)), 14L)
 
 dotest("1.10.1", length(fitted(madsen_fit1)), 3L)
 dotest("1.10.2", nobs(madsen_fit1), 3L)
@@ -290,5 +291,6 @@ dotest("1.10.12", names(anova(madsen_fit1, madsen_fit2)), c("Res.Df", "Res.Sum S
 dotest("1.10.13", dim(confint(madsen_fit1, parm = c(1L, 2L))), c(2L, 2L))
 dotest("1.10.14", dim(confintd(madsen_fit1, expr = quote(x1 - x2), dtype = "numeric")), c(1L, 3L))
 dotest("1.10.15", capture.output(madsen_fit1)[c(1, 2)], c("Nonlinear regression model", "  model: y ~ fn(x)"))
+dotest("1.10.16", length(hatvalues(madsen_fit1)), 3L)
 
 cat("Completed gslnls unit tests\n")

src/Makevars.win

@@ -0,0 +1,6 @@
+# use pkg-config conditionally to support older versions of Rtools
+ifeq (,$(shell pkg-config --version 2>/dev/null))
+   PKG_LIBS = -lgsl -lgslcblas -lm
+else
+   PKG_LIBS = $(shell pkg-config --libs gsl)
+endif