version 2.3.0

cran · Dec 23, 2017 · 09a138d · 09a138d
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,10 +1,10 @@
 Package: smooth
 Type: Package
 Title: Forecasting Using Smoothing Functions
-Version: 2.2.1
-Date: 2017-11-15
+Version: 2.3.0
+Date: 2017-12-23
 Authors@R: person("Ivan", "Svetunkov", email = "ivan@svetunkov.ru", role = c("aut", "cre"),
-                  comment="Lecturer at Lancaster Centre for Marketing Analytics and Forecasting, UK")
+                  comment="Lecturer at Centre for Marketing Analytics and Forecasting, Lancaster University, UK")
 URL: https://github.com/config-i1/smooth
 BugReports: https://github.com/config-i1/smooth/issues
 Description: The set of smoothing functions used for time series analysis and
@@ -19,9 +19,9 @@ Suggests: Mcomp, numDeriv, testthat, knitr, rmarkdown
 VignetteBuilder: knitr
 RoxygenNote: 6.0.1
 NeedsCompilation: yes
-Packaged: 2017-11-15 21:52:04 UTC; config
-Author: Ivan Svetunkov [aut, cre] (Lecturer at Lancaster Centre for Marketing
-    Analytics and Forecasting, UK)
+Packaged: 2017-12-23 18:21:22 UTC; config
+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: 2017-11-15 23:39:22 UTC
+Date/Publication: 2017-12-23 21:54:44 UTC
diff --git a/MD5 b/MD5
@@ -1,17 +1,17 @@
-512418a84cfb043e3c459321dd2c1018 *DESCRIPTION
-bb9381bb3841d8e3a43dc4c60dc58909 *NAMESPACE
-e4fbe276c18d3602e6b08cb6dc0ae2f9 *NEWS
+16ea8ff92c9e3b248d04e33e2e781004 *DESCRIPTION
+9cc90e0b5dd726cd1c43861041f6a01d *NAMESPACE
+b1fc1c2e5ba99eafd468fbdb40180d86 *NEWS
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@@ -20,53 +20,54 @@ a38a61c218e0c31e720c661377c1fd0e *R/simsma.R
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 f3ed0b0c8141601ade33960b4adaf625 *man/forecast.smooth.Rd
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 af48261bd26505868b5f69dc8f72d744 *man/graphmaker.Rd
 3639c7d4ce4e4a34cf963a692d1504de *man/hm.Rd
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 79d9433fe65351f998c5135409520b87 *man/orders.Rd
 32ba66fb55d350baeddf8fa8d2c7582a *man/pls.Rd
@@ -80,29 +81,30 @@ a88b6766e9af23292de6eb1a7198e96d *man/nParam.Rd
 d2a76be04301a6ee211d85327a2a60cf *man/sma.Rd
 ac3b74d8318d0056ffbc5cf6bec453ec *man/smooth.Rd
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 bc1c0a7cd81c16a8f24ac5a09018d621 *man/xregExpander.Rd
 9859afefaf6500832d7469cadbbb28c8 *src/Makevars
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 d110340e8c48ffeb684cbd4b16102480 *src/RcppExports.cpp
 9fb0915a4e7ffe192150808e5e890c69 *src/registerDynamicSymbol.c
-ae77cf25b22cc0a03378a1b8f81017fa *src/ssgeneralfun.cpp
-01456cf00361e634cbf7072cb8918f97 *src/vssGeneral.cpp
+618a04695dc72af516664b13c4f02c0c *src/ssgeneralfun.cpp
+d7ee89f14912b9bc39ff1c7b2da7a1e6 *src/vssGeneral.cpp
 4e0f43b23ba7abbb29b225614e88f276 *tests/testthat.R
 ce0c82d2b00807f0783cb0b472a4b5a1 *tests/testthat/test_ces.R
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 8d89e0ea91f860f5f587d8ac449fd441 *tests/testthat/test_ges.R
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 c9bc7f36d491e62c70cd1344ff6bbcf0 *tests/testthat/test_ves.R
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-a2cb1d397a0258d449763bfb68326f4b *vignettes/sma.Rmd
+9a6306fb84d1f4cf62fdecb1966aa0ab *vignettes/ces.Rmd
+7f2153c01ba2869e4d0f1f5185757840 *vignettes/es.Rmd
+492254727ba37b5e11e27e1653a96872 *vignettes/ges.Rmd
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 92af2e1ce4db47efe8a15dcb525d3350 *vignettes/smooth.Rmd
-5409f129b5ae093817e2411c239602e0 *vignettes/ssarima.Rmd
-3841e3e81d8b01ed2bb2dac7da3eb1c4 *vignettes/ves.Rmd
+34848d642b0687c7222197922f1a8ae3 *vignettes/ssarima.Rmd
+6c8b41018faa5597c4c3373c512a5e1e *vignettes/ves.Rmd
diff --git a/NAMESPACE b/NAMESPACE
@@ -12,34 +12,40 @@ S3method(lags,default)
 S3method(logLik,iss)
 S3method(logLik,smooth)
 S3method(logLik,smooth.sim)
+S3method(logLik,viss)
 S3method(modelType,default)
 S3method(modelType,vsmooth)
 S3method(nParam,default)
 S3method(nParam,iss)
 S3method(nParam,smooth)
+S3method(nParam,viss)
 S3method(nobs,iss)
 S3method(nobs,smooth)
 S3method(nobs,smooth.sim)
+S3method(nobs,viss)
 S3method(nobs,vsmooth)
 S3method(orders,Arima)
 S3method(orders,default)
 S3method(plot,iss)
 S3method(plot,smooth)
 S3method(plot,smooth.forecast)
 S3method(plot,smooth.sim)
+S3method(plot,viss)
 S3method(pointLik,default)
 S3method(pointLik,smooth)
 S3method(print,iss)
 S3method(print,smooth)
 S3method(print,smooth.forecast)
 S3method(print,smooth.sim)
+S3method(print,viss)
 S3method(print,vsmooth)
 S3method(sigma,smooth)
 S3method(sigma,vsmooth)
 S3method(simulate,smooth)
 S3method(summary,iss)
 S3method(summary,smooth)
 S3method(summary,smooth.forecast)
+S3method(summary,viss)
 S3method(summary,vsmooth)
 export(AICc)
 export(MAPE)
@@ -79,6 +85,7 @@ export(sowhat)
 export(ssarima)
 export(stepwise)
 export(ves)
+export(viss)
 export(xregExpander)
 import(Rcpp)
 import(zoo)

diff --git a/NEWS b/NEWS
@@ -1,3 +1,34 @@
+smooth v2.3.0 (Release data: 2017-12-23)
+==============
+
+Changes:
+* New function, viss() - vector intermittent state-space model. Allows modelling occurrence probability of several variables simultaneously.
+* New initialisation for es(), ges() and ces(). This should help getting more accurate initial states in cases of high frequency data.
+* The user can now control the optimiser via maxeval and xtol_rel provided in ellipsis of es() and ges() functions.
+
+Bugfixes:
+* smooth functions would return errors in case when some xreg variables were dropped and only one would be left.
+* ETSX(Z,Z,Z) did not work when xreg contained negative data. Now it should.
+* Number of parameters in case of xregDo="select" was incorrect.
+
+
+smooth v2.2.2 (Release data: 2017-12-15)
+==============
+
+Changes:
+* Updated vignettes.
+* New probability type for intermittent models - "logistic".
+* In the case when we don't have binary xreg for the holdout, we now consider it as random and forecast it using iss().
+* graphmaker() now only resets par() when legend=TRUE. This allows using layout and producing several plots with the function on one canvas.
+* xregExpander() now uses iss() function in case of binary data.
+* Updated an example in stepwise() function.
+* ves() function now uses warning() instead of message() everywhere.
+* iss() now also accepts and returns initialSeason (works with intermittent="l" only).
+
+Bugfixes:
+* Fixed Likelihood calculation for TSB probability model.
+
+
 smooth v2.2.1 (Release data: 2017-11-15)
 ==============
 

diff --git a/R/autoces.R b/R/autoces.R
@@ -57,7 +57,8 @@ auto.ces <- function(data, models=c("none","simple","full"),
                 cfType=c("MSE","MAE","HAM","MSEh","TMSE","GTMSE"),
                 h=10, holdout=FALSE, cumulative=FALSE,
                 intervals=c("none","parametric","semiparametric","nonparametric"), level=0.95,
-                intermittent=c("none","auto","fixed","interval","probability","sba"), imodel="MNN",
+                intermittent=c("none","auto","fixed","interval","probability","sba","logistic"),
+                imodel="MNN",
                 bounds=c("admissible","none"),
                 silent=c("all","graph","legend","output","none"),
                 xreg=NULL, xregDo=c("use","select"), initialX=NULL,

diff --git a/R/autoges.R b/R/autoges.R
@@ -57,7 +57,8 @@ auto.ges <- function(data, orderMax=3, lagMax=frequency(data), type=c("A","M","Z
                      cfType=c("MSE","MAE","HAM","MSEh","TMSE","GTMSE"),
                      h=10, holdout=FALSE, cumulative=FALSE,
                      intervals=c("none","parametric","semiparametric","nonparametric"), level=0.95,
-                     intermittent=c("none","auto","fixed","interval","probability","sba"), imodel="MNN",
+                     intermittent=c("none","auto","fixed","interval","probability","sba","logistic"),
+                     imodel="MNN",
                      bounds=c("admissible","none"),
                      silent=c("all","graph","legend","output","none"),
                      xreg=NULL, xregDo=c("use","select"), initialX=NULL,

diff --git a/R/ces.R b/R/ces.R
@@ -72,6 +72,7 @@ utils::globalVariables(c("silentText","silentGraph","silentLegend","initialType"
 #' \item \code{actuals} - The data provided in the call of the function.
 #' \item \code{holdout} - the holdout part of the original data.
 #' \item \code{imodel} - model of the class "iss" if intermittent model was estimated.
+#' If the model is non-intermittent, then imodel is \code{NULL}.
 #' \item \code{xreg} - provided vector or matrix of exogenous variables. If
 #' \code{xregDo="s"}, then this value will contain only selected exogenous
 #' variables.
@@ -141,7 +142,8 @@ ces <- function(data, seasonality=c("none","simple","partial","full"),
                 cfType=c("MSE","MAE","HAM","MSEh","TMSE","GTMSE"),
                 h=10, holdout=FALSE, cumulative=FALSE,
                 intervals=c("none","parametric","semiparametric","nonparametric"), level=0.95,
-                intermittent=c("none","auto","fixed","interval","probability","sba"), imodel="MNN",
+                intermittent=c("none","auto","fixed","interval","probability","sba","logistic"),
+                imodel="MNN",
                 bounds=c("admissible","none"),
                 silent=c("all","graph","legend","output","none"),
                 xreg=NULL, xregDo=c("use","select"), initialX=NULL,
@@ -419,7 +421,7 @@ CreatorCES <- function(silentText=FALSE,...){
         matw <- matrix(c(1,0),1,2);
         matvt <- matrix(NA,obsStates,2);
         colnames(matvt) <- c("level","potential");
-        matvt[1,] <- c(mean(yot[1:min(10,obsNonzero)]),mean(yot[1:min(10,obsNonzero)])/1.1);
+        matvt[1,] <- c(mean(yot[1:min(max(10,datafreq),obsNonzero)]),mean(yot[1:min(max(10,datafreq),obsNonzero)])/1.1);
     }
     else if(seasonality=="s"){
         # Simple seasonality, lagged CES
@@ -650,6 +652,10 @@ CreatorCES <- function(silentText=FALSE,...){
             colnames(matxt) <- colnames(matat) <- xregNames;
         }
         xreg <- matxt;
+        if(xregDo=="s"){
+            nParamExo <- FXEstimate*length(matFX) + gXEstimate*nrow(vecgX) + initialXEstimate*ncol(matat);
+            parametersNumber[1,2] <- nParamExo;
+        }
     }
 
 # Prepare for fitting
@@ -712,6 +718,9 @@ CreatorCES <- function(silentText=FALSE,...){
     else if(intermittent=="p"){
         intermittent <- "probability";
     }
+    else if(intermittent=="l"){
+        intermittent <- "logistic";
+    }
     else if(intermittent=="n"){
         intermittent <- "none";
     }