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@eeholmes eeholmes released this 05 Feb 04:28
· 790 commits to master since this release
v3.10.12
165c99d

Version 3.10.12 update mainly has to do with the tidy(), fitted() and augment() enhancements which clarify ytT, xtT and residual intervals for MARSS models. This was a major update though probably users won't notice much as it only affects residuals output. A few minor bugs were fixed which caused errors to be thrown in some rare time-varying cases. One bug that affected bootstrap confidence intervals was fixed. The documentation got a major clean-up. The Residuals report has been heavily edited to improve precision and clarity (with added verbosity). The help files and automated manual from the help files were cleaned-up and some of the internal functions moved out of the manual.

BUGS

  • MARSSsimulate() missing values were placed in the wrong positions in simulated data. This would affect all simulated data with missing values and thus any function that used MARSSboot(), for example bootstrap confidence intervals for a data set with missing values. Default is to use Hessian so the user would not normally have encountered this bug and it had little effect on the CIs.
  • fitted.marssMLE() Fixed bug in fitted.marssMLE for states when one.step.ahead=TRUE. It was using xtt1[,t-1] instead of xtt[,t-1]. The former meant it only used data up to t-2.
  • degen.test() in MARSSkem() was not catching when R or Q was time-varying (and thus degeneracy should not be allowed). Changed to test the 3D of model.dims == 1 or not.
  • residuals.marssMLE(..., Harvey=TRUE) would fail if Q, B, or G was time-varying because parmat() called with t+1. Changed to only call parmat() when t<TT. Q, B, and G do not appear in the recursion when t=TT so parmat() with t=t+1 is never needed.
  • MARSS_dfa() used form="dfa" in MARSS.call list. Just info. Never used.
  • Default A matrix ("scaling") was throwing an error for manually set up DLM models. Problem was call to check that Z was a design matrix in MARSS_marxss.R. It was not catching that Z was time-varying before running is.design().
  • toLatex.marssMODEL() Fixed some old bugs in toLatex_marssMODEL.R. Added S3 class declaration in NAMESPACE for toLatex. fixed equation attribute in MARSS_marxss. G{t} was used instead of G_{t}. Only affected toLatex_marssMODEL(). Had extra line in build.mat.tex() that removed last line of matrices. This function was not exported so users would never have run into these bugs.
  • MARSSkfss() To limit propogation of numerical errors when R=0, the row/col of Vtt for the fully determined x (determined from data) need to be set to 0. My algorithm for finding these x was not robust and zero-d out Vtt row/cols when it should not have if Z was under-determined. MARSSkfss() is not used for fitting and only affected underdetermined models (such as models with a stochastic trend and AR-1 errors). To fix I added a function fully.det.x() to the utility functions. This returns the x that are fully determined by the data. Note, MARSkfss() is the classic Kalman filter/smoother. The MARSS algorithm does not use this normally. Normally MARSSkfas(), build off the Koopman et al algorithm which avoids unneeded matrix inverses, is used. MARSSkfas() uses the Kalman filter/smoother in the KFAS package.

ENHANCEMENTS

  • MARSShatyt() Added ytt, ytt1, Ott, Ott1 to MARSShatyt() so that tidy.marssMLE() can more easily return the one-step-ahead preditions for Y(t). Also added var.ytT and var.EytT so you can easily get the estimates, CI and prediction intervals for missing data. Added only.kem to MARSShatyt() so that only values conditioned on 1:T as needed by MARSS kem are returned. This makes the Ey part of a MARSS object smaller and speeds up MARSShatyt() a little.
  • tidy.marssMLE() Changed type for tidy() to xtT, ytT and fitted.ytT. tidy() exclusively gives estimates of things (parameters, X, Y, fitted Y) conditioned on all the data.
  • fitted.marssMLE() Added interval=c("none", "confidence", "prediction") to fitted() and returns a list with se's (or sd's if prediction) and intervals. Also added conditioning argument to fitted.marssMLE which gives fitted values with different conditioning. Changed default output to tibble.
  • augment.marssMLE() Changed standard errors output for augment() to .se.fit for std error of fitted y and .sigma to std error of residuals. This matches what augment.lm outputs.
  • plot.marssMLE() and autoplot.marssMLE(). Added plot.par to plot.marssMLE and autoplot.marssMLE so that the plots can be customized. Added plot of ytT to both functions. Changed the residuals plots to use the CIs for the residuals not the loess CIs.
  • MARSSinfo() Added "AZR0" to MARSSinfo() to give info if user gets error that A cannot be estimated with R=0. Added more informative message to MARSSkemcheck() for that case.
  • Made all if statements checking class of object robust to the class returning more than one class (so vector of length > 1). Due to change in R 4.0.0 where matrix has class c("matrix","array")
  • Updated all code to tidyverse style
  • Changed residuals.marssMLE(). This is now a helper function which calls MARSSresiduals.tT() or MARSSresiduals.tt1(). The former is smoothation residuals and the latter is innovations (one-step-ahead) residuals.

DOCUMENTATION and MAN FILES

  • Added derivation of variance of Y conditioned on y and X to EMDerivation.Rnw. Needed for CI on the missing values estimate.
  • Major update to Residuals report. No changes to equations but much editting to improve precision and clarity (with much more verbosity). Reposted to Arxiv. Added innovations residuals.
  • tidy, augment and fitted man files got major update.
  • internal functions given \keyword{internal} so they don't appear in the documentation, but will appear if you use ? or help.search.
  • Rd files extensively cleaned to improve linking and move more of the internal functions out of view of the normal user. Equations cleaned up (though not completely).
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