Merge pull request #195 from atsa-es/Rd

vrs 3.11.9 to fix the Rd formatting issues

.Rbuildignore

@@ -4,6 +4,8 @@
 .Rhistory
 .RData
 .gitignore
+.git_diff_name-only
+.git_ls-tree_r_name-only_HEAD
 ^\.github$
 
 License.md

DESCRIPTION

@@ -2,7 +2,7 @@ Package: MARSS
 Type: Package
 Title: Multivariate Autoregressive State-Space Modeling
 Version: 3.11.9
-Date: 2023-05-20
+Date: 2024-02-19
 Depends: R (>= 3.5.0)
 Imports: 
     generics (>= 0.1.2), graphics, grDevices, KFAS (>= 1.0.1), mvtnorm, nlme, stats, utils
@@ -33,13 +33,13 @@ Description: The MARSS package provides maximum-likelihood parameter
     dynamic linear models, outlier and shock detection, and multivariate AR-p models.  
     Online workshops (lectures, eBook, and computer labs) 
     at <https://atsa-es.github.io/>.
-License: GPL-3 + file LICENSE
+License: GPL-2
 LazyData: yes
 BuildVignettes: yes
 ByteCompile: TRUE
 URL: https://atsa-es.github.io/MARSS/
 BugReports: https://github.com/atsa-es/MARSS/issues
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1
 Roxygen: list(markdown = TRUE)
 Encoding: UTF-8
 VignetteBuilder: knitr, utils

NEWS.md

@@ -2,12 +2,12 @@
 output: html_document
 ---
 
-# MARSS 3.11.9 (GitHub)
+# MARSS 3.11.9 (CRAN 2024-02-19)
 
-## ENHANCEMENT
+Very minor cosmetic update.
 
 * Added the error message coming from a try-error to the message printed for the user.
-* Updated to GPL-3 license.
+* Fixed some Rd formatting errors that caused NOTEs on CRAN.
 
 # MARSS 3.11.8 (CRAN 2023-05-20)
 

R/MARSS-methods.R

@@ -2,9 +2,9 @@
 #' 
 #' 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. 
+#' the marssTMB package 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.
+#' MARSS package or `MARSStmb()` in the marssTMB package.
 #' @param x a [marssMLE] object.
 #' @param ... additional arguments for the fitting function
 MARSSfit <- function(x, ...) {

R/MARSScv.R

@@ -11,7 +11,7 @@
 #' that specifies initial values for the parameters. See also [MARSS.marxss()].
 #' @param method Estimation method. MARSS provides an EM algorithm (`method="kem"`)
 #' (see [MARSSkem()]) and the BFGS algorithm (`method="BFGS"`)
-#' (see [MARSSoptim()]). Fast TMB fitting provided by the companion package {marssTMB}.
+#' (see [MARSSoptim()]). Fast TMB fitting provided by the companion package marssTMB.
 #' @param form The equation form used in the \code{MARSS()} call.  The default is "marxss".
 #' See [MARSS.marxss()] or [MARSS.dfa()]
 #' @param silent Setting to TRUE(1) suppresses printing of full error messages, warnings,

cran-comments.md

@@ -1,8 +1,10 @@
+This is a minor update to fix some formatting errors in Rd files.
+
 ## Tested on OS
 
-* `rhub::check_for_cran()`
+* `rhub::check_for_cran()` on tar.gz
 * M1 MacBook
-* R versions 4.3 and 4.2
+* R versions 4.3.2
 
 ## R CMD check results
 
@@ -21,20 +23,3 @@
 
 This is correct.
 
-─  checking CRAN incoming feasibility ... [20s] NOTE
-   Maintainer: 'Elizabeth Eli Holmes <[email protected]>'
-
-*  New maintainer:
-     Elizabeth Eli Holmes <[email protected]>
-   Old maintainer(s):
-     Elizabeth Holmes - NOAA Federal <[email protected]>
-
-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.
-
- * We saw 0 new problems
- * We failed to check 0 packages

inst/DEVELOPER_NOTES.md

@@ -4,7 +4,7 @@ The pkgdown webpage will be automatically updated whenever a push is made to the
 
 # Steps for a release
 
-Once a release is ready, all tests done and documentation checked, the Makefile in `inst/doc` is run. I usually run one target at a time starting with `make movetovignettes`. Before doing this, I build the User Guide and run it through a few compressors: Adobe and then https://github.com/atsa-es/pdfsizeopt-readme.
+Once a release is ready, all tests done and documentation checked, the Makefile in `inst/doc` is run. I usually run one target at a time starting with `make movetovignettes` then `make build` etc. This makefile will ensure that all the pieces of the tar.gz are in place. Before doing this, I build the User Guide and run it through a few compressors: Adobe and then https://github.com/atsa-es/pdfsizeopt-readme.
 
 ## Spellcheck the whole package
 

inst/Makefile

@@ -1,5 +1,5 @@
 RM = rm -f
-version = 3.11.8
+version = 3.11.9
 GitHubdir = ~/Documents/GitHub
 tmpdir = ~/Dropbox
 

inst/doc/Learning_MARSS.Rmd

@@ -0,0 +1,94 @@
+---
+title: "Learning MARSS"
+link-citations: yes
+pkgdown:
+  as_is: true
+output: 
+  rmarkdown::html_vignette: default
+  html_document: default
+vignette: >
+  %\VignetteIndexEntry{Learning MARSS}
+  %\VignetteEncoding{UTF-8}
+  %\VignetteEngine{knitr::rmarkdown}
+---
+
+The MARSS R package: <https://cran.r-project.org/package=MARSS> is part
+of the [Applied Time Series Analysis](https://atsa-es.github.io/) for
+Environmental Science suite of software and educational material for
+time series analysis. See the GitHub repository for the [MARSS source
+code](https://github.com/atsa-es/MARSS). For fast fitting to large datasets or DFA models, see our companion package, [marssTMB](https://atsa-es.github.io/marssTMB/). 
+<br>
+<br>
+
+# Documentation
+
+*   [MARSS pkgdown site](https://atsa-es.github.io/MARSS/).
+
+# Tutorials
+
+<img src="atsa-labs-cover.jpg" style="float: right;" width="40%"/>
+
+*   [Quick Start Guide](https://atsa-es.github.io/MARSS/articles/Quick_Start.html).
+*   [ATSA course website](https://atsa-es.github.io/atsa/) - We have
+    lectures and all material from our course on our course website.
+    Select the Lectures tab to find the lecture material and videos of
+    lectures.
+*   [ATSA lab book](https://atsa-es.github.io/atsa-labs/) - Many
+    applications are also covered in our Applied Time Series Analysis
+    book developed from the labs in our course.
+*   [2021 ATSA Lectures on
+    YouTube](https://www.youtube.com/playlist?list=PLA5yNsxyt7sC3B4qhj_sMgGWqWWaSerq-)
+*   The [User Guide on
+    CRAN](https://CRAN.R-project.org/package=MARSS/vignettes/UserGuide.pdf) included in the package has many examples of how to fit MARSS models to a variety of data sets.
+
+## For Statisticians
+
+For those who work on MARSS models. A good place to start might be the chapter at the end of the User Guide on the comparison of KFAS and MARSS outputs and terminology. Comparing the terminology between the two packages should help understanding the MARSS output. Similarly the chapter on StructTS will help understand the difference in notation and terminology.
+
+MARSS is designed to provide access to every possible conditional expectation of $\mathbf{X}$ and $\mathbf{Y}$. "Every possible" means all the temporal conditionings (time 1 to $t-1$, $t$ or $T$) and all the possible standardizations (none, marginal, Cholesky). It will return the standard errors for all of these combinations. The Residuals subsection in the KFAS chapter will compare the residual options in KFAS to the MARSS residuals. The KFAS terminology may be more familiar and a table in that chapter shows you what terminology is associated with what conditional expectation. Note, KFAS and MARSS give the same values. The difference is notation and terminology. 
+
+The EM Derivation paper goes into the nitty-gritty of the underlying EM algorithm. The Residuals paper goes through the Residuals algorithms. All the help files for the functions that implement algorithms have the details for statisticians/developers. My notes on computing the Fisher Information matrix for MARSS are in a series of notes: [Notes on computing the Fisher Information matrix for MARSS models I-IV](https://eeholmes.github.io/posts/2016-5-18-FI-recursion-1/).
+
+# CITATION
+
+If you use MARSS results in publications, please cite the primary
+citation:
+
+Holmes, E. E., Ward, E. J. and Wills, K. (2012) MARSS: Multivariate
+Autoregressive State-space Models for Analyzing Time-series Data. The R
+Journal. 4(1):11-19
+
+You can also cite the package and user guide:
+
+Elizabeth E. Holmes, Eric J. Ward, Mark D. Scheuerell and Kellie Wills
+(2023). MARSS: Multivariate Autoregressive State-Space Modeling. R
+package version 3.11.7.
+
+Holmes, E. E., M. D. Scheuerell, and E. J. Ward (", year,") Analysis of
+multivariate time-series using the MARSS package. Version ",
+meta\$Version,". NOAA Fisheries, Northwest Fisheries Science Center,
+2725 Montlake Blvd E., Seattle, WA 98112, DOI: 10.5281/zenodo.5781847
+
+Type `citation("MARSS")` at the command line to get the most up to data
+citations.
+
+### PUBLICATIONS {#pubs}
+
+To see our publications using MARSS models, see the [Applied Time Series
+Analysis website](https://atsa-es.github.io/).
+
+### NOAA Disclaimer
+
+The MARSS R package is a scientific product and is not official
+communication of the National Oceanic and Atmospheric Administration, or
+the United States Department of Commerce. All NOAA code is provided on
+an 'as is' basis and the user assumes responsibility for its use. Any
+claims against the Department of Commerce or Department of Commerce
+bureaus stemming from the use of this GitHub project will be governed by
+all applicable Federal law. Any reference to specific commercial
+products, processes, or services by service mark, trademark,
+manufacturer, or otherwise, does not constitute or imply their
+endorsement, recommendation or favoring by the Department of Commerce.
+The Department of Commerce seal and logo, or the seal and logo of a DOC
+bureau, shall not be used in any manner to imply endorsement of any
+commercial product or activity by DOC or the United States Government.