version 2.6.0

cran · Jun 17, 2020 · 5a8da09 · 5a8da09
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,8 +1,8 @@
 Package: smooth
 Type: Package
 Title: Forecasting Using State Space Models
-Version: 2.5.6
-Date: 2020-03-31
+Version: 2.6.0
+Date: 2020-06-16
 Authors@R: person("Ivan", "Svetunkov", email = "ivan@svetunkov.ru", role = c("aut", "cre"),
                   comment="Lecturer at Centre for Marketing Analytics and Forecasting, Lancaster University, UK")
 URL: https://github.com/config-i1/smooth
@@ -23,12 +23,12 @@ Imports: Rcpp (>= 0.12.3), stats, graphics, forecast (>= 7.0), nloptr,
 LinkingTo: Rcpp, RcppArmadillo (>= 0.8.100.0.0)
 Suggests: Mcomp, numDeriv, testthat, knitr, rmarkdown
 VignetteBuilder: knitr
-RoxygenNote: 7.0.2
+RoxygenNote: 7.1.0
 Encoding: UTF-8
 NeedsCompilation: yes
-Packaged: 2020-04-04 16:18:34 UTC; config
+Packaged: 2020-06-16 10:00:33 UTC; isvetunkov
 Author: Ivan Svetunkov [aut, cre] (Lecturer at Centre for Marketing Analytics
     and Forecasting, Lancaster University, UK)
 Maintainer: Ivan Svetunkov <ivan@svetunkov.ru>
 Repository: CRAN
-Date/Publication: 2020-04-05 05:00:06 UTC
+Date/Publication: 2020-06-17 04:10:03 UTC
diff --git a/MD5 b/MD5
@@ -1,104 +1,106 @@
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-7abc2e3841ba1acdbba753e4fb4d763f *NAMESPACE
-0851f7a72b2e05700b0abc9895037ac6 *NEWS
+4e19c32dbd7d9b6b555ddf2b8e1c4b73 *DESCRIPTION
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 0f3268c8a858c058a3fa8b8939767d2e *man/orders.Rd
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 de254074c413aa1440d8dbebffb6aef6 *man/sma.Rd
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 457aa83914d2fd574c3e0bced7e8a69d *man/smoothCombine.Rd
 a0993d7de7f0b96415bb7b69f66b60ab *man/sowhat.Rd
-7da59a7b3a4333c62f89be0516041a57 *man/ssarima.Rd
-9d9e83c1adf03481fb271ffca5b9b114 *man/ves.Rd
-4f1c3c4ede7369b0435ad6c20cb7cf1a *man/viss.Rd
+00e8688673c5c2f5d9f3211776e24570 *man/ssarima.Rd
+3df0888e4f417e2f0924b0bfa36a6409 *man/ves.Rd
+056df94fe40fc4a2b274c11ed39da16e *man/viss.Rd
 9859afefaf6500832d7469cadbbb28c8 *src/Makevars
 a6850c2998c396b505104b800670480e *src/Makevars.win
 d736b0ac3c57296a62ff17c520142d0c *src/RcppExports.cpp
@@ -111,18 +113,18 @@ cccddc1650403630c1f85f6bc9a2ac63 *src/ssSimulator.cpp
 3ff978aed1beb78736800b0bf9e709d1 *src/vssGeneral.cpp
 4e0f43b23ba7abbb29b225614e88f276 *tests/testthat.R
 637bec64c17967aa1c4454bd1a51ddd5 *tests/testthat/test_ces.R
-f925ba8597ccf07763fb7b851122455c *tests/testthat/test_es.R
-02ac837d0ec958cbdd82441b4c0e54d4 *tests/testthat/test_ges.R
+cdea51cf57338acfcad9d58e5cc323f8 *tests/testthat/test_es.R
+3f799babe2468f6c965b9bc322d380d0 *tests/testthat/test_ges.R
 f4e352807360804369ed3b29e359668d *tests/testthat/test_oes.R
-f152728a5b15d9b65d9f46cade8552e0 *tests/testthat/test_simulate.R
+40a67520d44188ca73484f46f7961216 *tests/testthat/test_simulate.R
 84b5bd3ad4f998695404cf76b9fef734 *tests/testthat/test_ssarima.R
 8d83197fe52352a1f5fbc316db36929a *tests/testthat/test_ves.R
 63102e1de32a1dfa9fca0c23576696a1 *vignettes/ces.Rmd
 75d528e227579a8662d15950b92d6d55 *vignettes/es.Rmd
 c757d7f4971db027d931c0543d77f79b *vignettes/gum.Rmd
 d5c5cdaf1dcb23ce35182bc1d846ef63 *vignettes/library.bib
-9e58b4b6fccc5835d175db183a852768 *vignettes/oes.Rmd
-3c284a1692f90426fba996c01a78af8c *vignettes/simulate.Rmd
+a26c9d64823db6948fe629afb4fe2cbb *vignettes/oes.Rmd
+df88acb4d0ba96f371e37c36fc256117 *vignettes/simulate.Rmd
 7a6cd5f84b090d58c565b781c2801327 *vignettes/sma.Rmd
 f2be0cff7be52faff06f2a377333a8c6 *vignettes/smooth-Documentation.pdf
 5c4f76203817ca1fd96b78ede52a9183 *vignettes/smooth.Rmd

diff --git a/NAMESPACE b/NAMESPACE
@@ -66,6 +66,7 @@ S3method(orders,smooth)
 S3method(orders,smooth.sim)
 S3method(plot,msdecompose)
 S3method(plot,oes)
+S3method(plot,oes.sim)
 S3method(plot,smooth)
 S3method(plot,smooth.forecast)
 S3method(plot,smooth.sim)
@@ -79,6 +80,7 @@ S3method(pointLik,smooth)
 S3method(print,iss)
 S3method(print,msdecompose)
 S3method(print,oes)
+S3method(print,oes.sim)
 S3method(print,smooth)
 S3method(print,smooth.forecast)
 S3method(print,smooth.sim)
@@ -136,6 +138,7 @@ export(pls)
 export(sim.ces)
 export(sim.es)
 export(sim.gum)
+export(sim.oes)
 export(sim.sma)
 export(sim.ssarima)
 export(sim.ves)

diff --git a/NEWS b/NEWS
@@ -1,3 +1,31 @@
+smooth v2.6.0 (Release data: 2020-06-16)
+=======
+
+Changes:
+* sim.oes() function, generating probability of occurrence and respective binary variable ot.
+* Tuning of ves() function and a couple of new parameters in ellipsis, that allow regulating the optimiser.
+* forecast.smooth() now allows specifying side of prediction interval. Note that this might not work well in cases of occurrence model.
+* Make ACF / PACF in plot.smooth() easier to read + tuning in case of non-ts objects.
+* sim.* functions now use proper do.call() instead of weird parse(...).
+* Initial smoothing parameters in oes() and oesg() are now set to 0.01 instead of 0.05. This should allow avoiding several cases of wrong optimisation.
+
+Bugfixes:
+* A weird glitch for occurrence model, when h=1: multiplication of yForecast by pForecast could not be done.
+* es() would not work in case of predefined persistence and initial, but not inisialSeason.
+* Model selection would not work in oes() for some types of models.
+* oesg() did not return class "occurrence".
+* A fix in sim.oes() for the ts() class in occurrence="inverse-odds-ratio".
+* oesg() now reports the correct type of model, not the abbreviation.
+* A fix for auto.ces(), which did not work on zeroes data.
+
+
+smooth v2.5.7 (Release data: 2020-04-06)
+==============
+
+Changes:
+* plot.smooth() now also produces standardised and studentised residuals over time.
+
+
 smooth v2.5.6 (Release data: 2020-03-31)
 ==============
 

diff --git a/R/autoces.R b/R/autoces.R
@@ -175,7 +175,7 @@ auto.ces <- function(y, models=c("none","simple","full"),
     }
 
     CESModel <- as.list(models);
-    IC.vector <- c(1:length(models));
+    ICs <- c(1:length(models));
 
     j <- 1;
     if(!silentText){
@@ -194,11 +194,11 @@ auto.ces <- function(y, models=c("none","simple","full"),
                              bounds=bounds, silent=TRUE,
                              xreg=xreg, xregDo=xregDo, initialX=initialX,
                              updateX=updateX, persistenceX=persistenceX, transitionX=transitionX, FI=FI);
-        IC.vector[j] <- CESModel[[j]]$ICs[ic];
+        ICs[j] <- CESModel[[j]]$ICs[ic];
         j <- j+1;
     }
 
-    bestModel <- CESModel[[which(IC.vector==min(IC.vector))]];
+    bestModel <- CESModel[[which(ICs==min(ICs))[1]]];
 
     yFitted <- bestModel$fitted;
     yForecast <- bestModel$forecast;
@@ -207,9 +207,9 @@ auto.ces <- function(y, models=c("none","simple","full"),
     modelname <- bestModel$model;
 
     if(!silentText){
-        best.seasonality <- models[which(IC.vector==min(IC.vector))];
+        bestModelType <- models[which(ICs==min(ICs))[1]];
         cat(" \n");
-        cat(paste0('The best model is with seasonality = "',best.seasonality,'"\n'));
+        cat(paste0('The best model is with seasonality = "',bestModelType,'"\n'));
     }
 
 ##### Make a plot #####

diff --git a/R/es.R b/R/es.R
@@ -303,15 +303,15 @@ es <- function(y, model="ZZZ", persistence=NULL, phi=NULL,
             persistence <- model$persistence[,i];
             initial <- model$initial[,i];
             initialSeason <- model$initialSeason[,i];
-            if(any(model$iprob!=1)){
+            if(any(model$probability!=1)){
                 occurrence <- "a";
             }
         }
         else{
             persistence <- model$persistence;
             initial <- model$initial;
             initialSeason <- model$initialSeason;
-            if(any(model$iprob!=1)){
+            if(any(model$probability!=1)){
                 occurrence <- "a";
             }
         }
@@ -733,8 +733,6 @@ EstimatorES <- function(...){
     }
 
     # Parameters are chosen to speed up the optimisation process and have decent accuracy
-    # res <- optimx::hjn(B, CF, lb, ub);
-    # B[] <- res$par;
     res <- nloptr(B, CF, lb=lb, ub=ub,
                   opts=list("algorithm"="NLOPT_LN_BOBYQA", "xtol_rel"=xtol_rel, "maxeval"=maxeval, print_level=0));
     B[] <- res$solution;
@@ -1688,7 +1686,7 @@ CreatorES <- function(silent=FALSE,...){
     }
 
 ##### Define modelDo #####
-    if(any(persistenceEstimate, (initialType=="o"), initialSeasonEstimate*(initialType=="o"),
+    if(any(persistenceEstimate, (initialType=="o"), initialSeasonEstimate,
            phiEstimate, FXEstimate, gXEstimate, initialXEstimate)){
         if(all(modelDo!=c("select","combine"))){
             modelDo <- "estimate";