Merge pull request #186 from atsa-es/v3-11-7

done with next CRAN release (hopefully)

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: MARSS
 Type: Package
 Title: Multivariate Autoregressive State-Space Modeling
-Version: 3.11.7
+Version: 3.11.8
 Date: 2023-05-20
 Depends: R (>= 3.5.0)
 Imports: 

NAMESPACE

@@ -50,6 +50,7 @@ importFrom(generics,tidy)
 
 ## register S3 methods
 export(MARSSfit) # method
+S3method(MARSSfit, default)
 S3method(MARSSfit, kem)
 S3method(MARSSfit, BFGS)
 

NEWS.md

@@ -2,7 +2,11 @@
 output: html_document
 ---
 
-# MARSS 3.11.7 (GitHub)
+# MARSS 3.11.8 (CRAN 2023-05-20)
+
+This combines the changes in GitHub releases 3.11.7 and 3.11.6.
+
+# MARSS 3.11.7 (GitHub 2023-05-19)
 
 This release is focused on moving the MARSS User Guide and derivation files into a `inst/userguide` and `inst/derivations` along with Makefiles to build. This will facilitate updating MARSS and converting the User Guide to an eBook.
 
@@ -26,6 +30,10 @@ This release is focused on moving the MARSS User Guide and derivation files into
 * Added `inst/DEVELOPER_NOTES.md`
 * Minor change to make the v and w in `EMDerivation.Rnw` in slant font as they are random variables.
 
+## OTHER
+
+* renamed `all.equal.vector` to `vector.all.equal()` so it is not interpreted as a method of `all.equal()`.
+
 
 # MARSS 3.11.6 (GitHub)
 

R/MARSS-methods.R

@@ -1,14 +1,18 @@
 #' Generic for fitting MARSS models
 #' 
-#' Uses the method of a marssMLE class object. Will call a function such as [MARSSkem()], [MARSSoptim()] or `MARSStmb()` in the {marssTMB} package.
+#' This is an internal function used by [MARSS()]. It is not
+#' intended for use by users but needs to be exported so
+#' {marssTMB} can use it. Uses the method of a marssMLE class object. 
+#' Will call a function such as [MARSSkem()], [MARSSoptim()] in the 
+#' MARSS package or `MARSStmb()` in the {marssTMB} package.
 #' @param x a [marssMLE] object.
 #' @param ... additional arguments for the fitting function
 MARSSfit <- function(x, ...) {
   UseMethod("MARSSfit")
 }
 
 MARSSfit.default <- function(x, ...){
-  stop("MARSS: Something is wrong. Did not find a method for the marssMLE object. Is method set incorrectly?\n There must be a MARSSfit.<method>() function for each method.")
+  stop("MARSS: Something is wrong. Did not find a method for the marssMLE object. The first element of the call of the object should be the method. Did you call MARSSfit() with a marssMLE object? You need to add the method as the first element of the class.")
 }
 
 MARSSfit.kem <- function(x, ...) MARSSkem(x)

R/toLatex_marssMODEL.R

@@ -369,7 +369,7 @@ build.eqn.tex <- function(eqn, eqn.special, x, greek, digits, simplify, headfoot
               # The following tests for that
               mat2D <- array(mat, dim = c(dim(mat)[1] * dim(mat)[2], dim(mat)[3])) # reform to be 2D
               # test equality within row; will return TRUE if dim 3 = 1
-              if (all(apply(mat, 1, all.equal.vector))) { # not time-varying
+              if (all(apply(mat, 1, vector.all.equal))) { # not time-varying
                 mat <- sub3D(mat, t = 1) # not time-varying so just use the mat at t=1
               } else { # is time-varying
                 if (!simplify) { # then there will be an equation for each parameter at time t
@@ -378,7 +378,7 @@ build.eqn.tex <- function(eqn, eqn.special, x, greek, digits, simplify, headfoot
                 } else { # do simplify
                   # step 1: figure out which parameter elements are time-varying
                   mat2D <- array(mat, dim = c(dim(mat)[1] * dim(mat)[2], dim(mat)[3])) # reform to be 2D, matrix(vec(mat),t)
-                  tv.elem <- !apply(mat2D, 1, all.equal.vector) # which elements are time varying
+                  tv.elem <- !apply(mat2D, 1, vector.all.equal) # which elements are time varying
                   # step 2: replace that element with the name el2(i)_t
                   tv.name <- paste(el2, "(", 1:dim(mat2D)[1], ")_", el2.time, sep = "")
                   # step 3: set up a mat to be t=1; will replace time=varying ones
@@ -443,9 +443,9 @@ parameters.time.varying <- function(eqn, eqn.special, x) {
       if (model.dims[[el2]][3] == 1) next # it is not time-varying
       # Even if 3D, it might not be time-varying if all elements are the same
       testtv <- FALSE
-      if (!all(apply(fixed[[el2]], 1, all.equal.vector))) testtv <- TRUE # time-varying
+      if (!all(apply(fixed[[el2]], 1, vector.all.equal))) testtv <- TRUE # time-varying
       mat2D <- array(free[[el2]], dim = c(dim(free[[el2]])[1] * dim(free[[el2]])[2], dim(free[[el2]])[3]))
-      if (!all(apply(mat2D, 1, all.equal.vector))) testtv <- TRUE # time-varying
+      if (!all(apply(mat2D, 1, vector.all.equal))) testtv <- TRUE # time-varying
       if (!testtv) { # not time-varying
         next
       } else {

R/utility_functions.R

@@ -869,7 +869,7 @@ is.solvable <- function(A, y = NULL) {
   return("unique")
 }
 
-all.equal.vector <- function(x) {
+vector.all.equal <- function(x) {
   all(sapply(as.list(x[-1]), FUN = function(z) {
     identical(z, unlist(x[1]))
   }))

cran-comments.md

@@ -1,3 +1,9 @@
+## Tested on OS
+
+* `rhub::check_for_cran()`
+* M1 MacBook
+* R versions 4.3 and 4.2
+
 ## R CMD check results
 
 0 errors | 0 warnings | 3 notes
@@ -7,22 +13,13 @@
     sub-directories of 1Mb or more:
       doc   4.6Mb
 
-* checking DESCRIPTION meta-information ... NOTE
-  Maintainer field differs from that derived from Authors@R
-    Maintainer: ‘Elizabeth Holmes - NOAA Federal <[email protected]>’
-    Authors@R:  ‘Elizabeth Eli Holmes <[email protected]>’
-
-For auto-check of the email that submission comes from, I use the form that my work email uses.
-
-* checking CRAN incoming feasibility ... NOTE
-  Maintainer: ‘Elizabeth Holmes - NOAA Federal <[email protected]>’
 
 *   Suggests or Enhances not in mainstream repositories:
      marssTMB
    Availability using Additional_repositories specification:
      marssTMB   yes   https://atsa-es.r-universe.dev
 
-    This is correct.
+This is correct.
 
 ─  checking CRAN incoming feasibility ... [20s] NOTE
    Maintainer: 'Elizabeth Eli Holmes <[email protected]>'
@@ -32,13 +29,9 @@ For auto-check of the email that submission comes from, I use the form that my w
    Old maintainer(s):
      Elizabeth Holmes - NOAA Federal <[email protected]>
 
-  Correct.
-
-   Possibly misspelled words in DESCRIPTION:
-     TMB (23:89)
-     marssTMB (24:16)
-
-     
+Correct. I changed to using Authors@R format
+
+
 ## revdepcheck results
 
 We checked 2 reverse dependencies, comparing R CMD check results across CRAN and dev versions of this package.

inst/DEVELOPER_NOTES.md

@@ -154,6 +154,8 @@ These are the tests in `tests/testthat`. All should pass but some give warnings.
 cd inst
 make
 ```
+However I usually run it one target at a time.
+
 
 Now using the final tar.gz file do the final tests.
 
@@ -165,10 +167,6 @@ rm -r ~/Dropbox/MARSS.Rcheck
 R CMD check --timings --as-cran MARSS_3.11.7.tar.gz
 ```
 
-
-However I usually run it one target at a time.
-
-
 ## Check on other OS
 
 * [ ] `devtools::check_win_devel()`

inst/Makefile

@@ -1,5 +1,5 @@
 RM = rm -f
-version = 3.11.7
+version = 3.11.8
 GitHubdir = ~/Documents/GitHub
 tmpdir = ~/Dropbox
 
@@ -24,12 +24,14 @@ build:
 	rm -r -f ${tmpdir}/MARSS
 	rm -f ${tmpdir}/MARSS_${version}.tar.gz
 	cp -p $(GitHubdir)/MARSS_${version}.tar.gz ${tmpdir}/MARSS_${version}.tar.gz
+	cd $(tmpdir) && tar -xvzf ${tmpdir}/MARSS_${version}.tar.gz
 
 movetodoc:
-	cd $(tmpdir) && tar -xvzf ${tmpdir}/MARSS_${version}.tar.gz
 	rm -f ${tmpdir}/MARSS/inst/doc/*.pdf
 	cp -a -p ${GitHubdir}/MARSS/inst/derivations/doc/*.pdf ${tmpdir}/MARSS/inst/doc
 	cp -a -p ${GitHubdir}/MARSS/inst/userguide/doc/. $(tmpdir)/MARSS/inst/doc/
+	cp -a -p ${GitHubdir}/MARSS/inst/derivations/doc/. ${GitHubdir}/MARSS/inst/doc/
+	cp -a -p ${GitHubdir}/MARSS/inst/userguide/doc/. $(GitHubdir)/MARSS/inst/doc/
 
 rebuild:
 	cd $(tmpdir) && R CMD build --no-build-vignettes MARSS

inst/derivations/Residuals-concordance.tex

@@ -0,0 +1,2 @@
+\Sconcordance{concordance:Residuals.tex:Residuals.Rnw:%
+1 175 1 1 0 628 1}

inst/derivations/Residuals.bbl

@@ -0,0 +1,38 @@
+\begin{thebibliography}{}
+
+\bibitem[Commandeur and Koopman, 2007]{CommandeurKoopman2007}
+Commandeur, J.~J. and Koopman, S.~J. (2007).
+\newblock {\em An introduction to state space time series analysis}.
+\newblock Practical Econometrics. Oxford University Press, Oxford.
+
+\bibitem[de~Jong, 1988]{deJong1988}
+de~Jong, P. (1988).
+\newblock A cross-validation filter for time series models.
+\newblock {\em Biometrika}, 75(3):594--600.
+
+\bibitem[de~Jong and Penzer, 1998]{deJongPenzer1998}
+de~Jong, P. and Penzer, J. (1998).
+\newblock Diagnosing shocks in time series.
+\newblock {\em Journal of the American Statistical Association}, 93(442):796--806.
+
+\bibitem[Harvey and Koopman, 1992]{HarveyKoopman1992}
+Harvey, A. and Koopman, S.~J. (1992).
+\newblock Diagnostic checking of unobserved-components time series models.
+\newblock {\em Journal of Business and Economic Statistics,}, 10:377--389.
+
+\bibitem[Harvey et~al., 1998]{Harveyetal1998}
+Harvey, A., Koopman, S.~J., and Penzer, J. (1998).
+\newblock Messy time series: a unified approach.
+\newblock {\em Advances in Econometrics}, 13:103--143.
+
+\bibitem[Holmes, 2012]{Holmes2010}
+Holmes, E.~E. (2012).
+\newblock Derivation of the {EM} algorithm for constrained and unconstrained {MARSS} models.
+\newblock Technical report, arXiv:1302.3919 [stat.ME].
+
+\bibitem[Shumway and Stoffer, 2006]{ShumwayStoffer2006}
+Shumway, R. and Stoffer, D. (2006).
+\newblock {\em Time series analysis and its applications}.
+\newblock Springer-Science+Business Media, LLC, New York, New York, 2nd edition.
+
+\end{thebibliography}