Ready for CRAN update

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: galamm
 Title: Generalized Additive Latent and Mixed Models
-Version: 0.1.1.9000
+Version: 0.2.0
 Authors@R: c(
     person(given = "Øystein",
            family = "Sørensen",

cran-comments.md

@@ -1,81 +1,20 @@
 ## Submission note
 
-This is a resubmission aimed at fixing current issues. There are three types of 
-issues, and the respective fixes are described under each header below:
-
-### 1. Memory issues (clang-ASAN, gcc-ASAN, valgrind)
-
-I was able to reproduce the error both using debug mode locally with 'R -d lldb'
-and using the Docker image rocker/r-devel-san. 
-The issue was caused by attempting to access a vector element at a an index 
-'-2', which clearly does not work. This case has now been fixed, and the fix is 
-described in more detail here: https://github.com/LCBC-UiO/galamm/issues/165.
-
-### 2. Errors on r-oldrelease
-
-I here explain why the failure happened, and how it has been fixed.
-
-Letting 'fam' be some model family, e.g., 'fam <- binomial()' or 
-'fam <- gaussian()', I had a test 'is.na(fam$dispersion)'. In R4.2.3 these 
-'fam' objects would not have an element named 'dispersion', and would cause a
-fail. In R4.3.1 'fam' does have a 'dispersion' element, and
-hence the test passed here. I have rewritten the code so it does not rely on
-this element, and verified it using devtools::test_win_oldrelease(). The fix
-is described in more detail here: https://github.com/LCBC-UiO/galamm/issues/167.
-
-### 3. Errors on M1 Mac
-
-On M1 Mac, 10 tests are skipped and 1 test fails. The failing test happens
-because the expected deviance value differs from the computed deviance value
-at 3rd decimal (885.7339 vs 885.7341). I have thus reduced the tolerance of this
-test, and also confirmed that the version now being submitted works with the 
-R Mac Builder (test outputs provided below).
-
+This is an update to the package which contains bug fixes, improvements of 
+the code base, and more documentation and examples.
 
 ## Test environments
 
 * R development version with sanitizer support via rocker/r-devel-san.
+* R 4.3.1 build with valgrind on a local Ubuntu 22.04.
 * R Mac Builder (https://mac.r-project.org/macbuilder/submit.html)
 * Windows, r-release, r-oldrelease, r-devel.
-* Local Apple M1 Max in debug mode (R -d lldb) on R4.3.1.
-* Local Apple M1 Max, on R4.3.1 and R4.2.3.
+* Local Apple M1 Max, on R4.3.3.
 * R-CMD-check via GitHub Actions on windows-latest, macOS-latest, 
   ubuntu-20.04 (release), and ubuntu-20.04 (devel).
 
 
 ## R CMD check results
 
-### r-devel-san
-
-0 ERRORs, 0 WARNINGs, 0 NOTEs
-
-### R Mac Builder
-
-0 ERRORs, 0 WARNINGs, 1 NOTE:
-
-* checking installed package size ... NOTE
-  installed size is 24.1Mb
-  sub-directories of 1Mb or more:
-    doc    1.9Mb
-    libs  21.1Mb
-
-### Windows, r-release, r-oldrelease, r-devel
-
-0 ERRORs, 0 WARNINGs, 1 NOTE:
-
-* checking CRAN incoming feasibility ... [15s] NOTE
-Maintainer: 'Øystein Sørensen <oystein.sorensen@psykologi.uio.no>'
-
-Days since last update: 4
-
-### Local Apple M1 Max in debug model (R -d lldb)
-
-0 ERRORs, 0 WARNINGs, 0 NOTEs
-
-### Local Apple M1 Max, on R4.3.1 and R4.2.3.
-
-0 ERRORs, 0 WARNINGs, 0 NOTEs
-
-### GitHub Actions
+There were 0 ERRORs, 0 WARNINGs, 0 NOTEs
 
-0 ERRORs, 0 WARNINGs, 0 NOTEs

data-raw/lifespan.R

@@ -1,17 +1,28 @@
 # Simulate lifespan data from Section 4.1 in Sørensen et al. (2023)
 library(tidyverse)
 library(mvtnorm)
+library(mgcv)
 set.seed(3)
 trajectories <- readRDS("data-raw/trajectories.rds")
+
+# Fix trajectory for executive function:
+mod <- gam(execfun_trajectory ~ s(age),
+           data = filter(trajectories, age < 25 | age > 50))
+
+# Fix trajectory for episodic memory:
+mod2 <- gam(epmem_trajectory ~ s(age),
+            data = filter(trajectories, age < 40 | age > 70))
+plot(mod2)
+
 epmem_fun <- approxfun(
   trajectories$age,
-  trajectories$epmem_trajectory
+  predict(mod2, newdata = trajectories)
 )
 wmem_fun <- approxfun(
   trajectories$age, trajectories$wmem_trajectory
 )
 execfun_fun <- approxfun(
-  trajectories$age, trajectories$execfun_trajectory
+  trajectories$age, predict(mod, newdata = trajectories)
 )
 
 n_ids <- 1000

news.md

@@ -1,4 +1,4 @@
-# galamm (development versions)
+# galamm version 0.2.0
 
 - The print.summary.galamm() method does no longer print residual percentiles 
   with mixed response models. The version implemented until now had a bug, and