Hello, This does what you want.
rownames(as.data.frame(TSSeriesModel1Forecast)) Hope this helps, Rui Barradas Em 15-03-2017 16:24, Paul Bernal escreveu:
Hello Rui, I have attached the .csv file, I will attach it again. Please let me know if you can access it. Cheers, Paul 2017-03-15 11:05 GMT-05:00 Rui Barradas <ruipbarra...@sapo.pt <mailto:ruipbarra...@sapo.pt>>: Hello, Since we don't have access to file ContainerDataNEW.csv I cannot say for sure but it seems that those dates are the rownames so you could try rownames(TSSeriesModel1Forecast) and see what it gives. Or I might be completely mistaken. Hope this helps, Rui Barradas Em 15-03-2017 15:50, Paul Bernal escreveu: Dear all, I am currently using R for windows Version 3.3.3 (I will provide the sessionInfo() output below) library("Rcmdr") Loading required package: splines Loading required package: RcmdrMisc Loading required package: car Loading required package: sandwich Rcmdr Version 2.3-2 library(forecast) library(tseries) 'tseries' version: 0.10-35 'tseries' is a package for time series analysis and computational finance. See 'library(help="tseries")' for details. library(stats) library(stats4) Data<-read.csv("ContainerDataNEW.csv") TSData<-ts(Data[,1], start=c(1985,10), frequency=12) TSeriesModel1<-ets(TSData) TSSeriesModel1Forecast<-forecast(TSeriesModel1,h=24) Now the output from forecasts is the following: Point Forecast Lo 80 Hi 80 Lo 95 Hi 95 Apr 2017 67.62845 30.73747 104.5194 11.20856 124.0483 May 2017 67.62845 30.73747 104.5194 11.20856 124.0483 Jun 2017 67.62845 30.73747 104.5194 11.20856 124.0483 Jul 2017 67.62845 30.73747 104.5194 11.20856 124.0483 Aug 2017 67.62845 30.73747 104.5194 11.20856 124.0483 Sep 2017 67.62845 30.73747 104.5194 11.20856 124.0483 Oct 2017 67.62845 30.73747 104.5194 11.20856 124.0483 Nov 2017 67.62845 30.73747 104.5194 11.20856 124.0483 Dec 2017 67.62845 30.73747 104.5194 11.20856 124.0483 Jan 2018 67.62845 30.73747 104.5194 11.20856 124.0483 Feb 2018 67.62845 30.73747 104.5194 11.20856 124.0483 Mar 2018 67.62845 30.73747 104.5194 11.20856 124.0483 Apr 2018 67.62845 30.73747 104.5194 11.20856 124.0483 May 2018 67.62845 30.73747 104.5194 11.20856 124.0483 Jun 2018 67.62845 30.73747 104.5194 11.20856 124.0483 Jul 2018 67.62845 30.73747 104.5194 11.20856 124.0484 Aug 2018 67.62845 30.73747 104.5194 11.20856 124.0484 Sep 2018 67.62845 30.73747 104.5194 11.20856 124.0484 Oct 2018 67.62845 30.73747 104.5194 11.20856 124.0484 Nov 2018 67.62845 30.73747 104.5194 11.20856 124.0484 Dec 2018 67.62845 30.73747 104.5194 11.20856 124.0484 Jan 2019 67.62845 30.73747 104.5194 11.20856 124.0484 Feb 2019 67.62845 30.73747 104.5194 11.20856 124.0484 Mar 2019 67.62845 30.73747 104.5194 11.20856 124.0484 However, as you can see, the first "column" contains the dates for the forecasts, but it appears as a field with no name. What I would like to do is to get those dates, add them as an additional column to the forecasts so that when I use the data.frame(Forecasts) I can have a result in this fashion: Date Point Forecast Lo 80 Hi 80 Lo 95 Hi 95 Apr 2017 67.62845 30.73747 104.5194 11.20856 124.0483 Is there a way to do this? Here is the sessionInfo() output: sessionInfo() R version 3.3.3 (2017-03-06) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 8.1 x64 (build 9600) locale: [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252 LC_NUMERIC=C LC_TIME=English_United States.1252 attached base packages: [1] stats4 splines stats graphics grDevices utils datasets methods base other attached packages: [1] tseries_0.10-35 forecast_8.0 Rcmdr_2.3-2 RcmdrMisc_1.0-5 sandwich_2.3-4 car_2.1-3 loaded via a namespace (and not attached): [1] Rcpp_0.12.7 lattice_0.20-34 tcltk2_1.2-11 class_7.3-14 zoo_1.7-13 lmtest_0.9-35 relimp_1.0-5 assertthat_0.1 digest_0.6.11 R6_2.2.0 plyr_1.8.4 [12] acepack_1.4.1 MatrixModels_0.4-1 e1071_1.6-7 httr_1.2.1 ggplot2_2.2.0 lazyeval_0.2.0 AzureML_0.2.13 curl_2.2 uuid_0.1-2 readxl_0.1.1 minqa_1.2.4 [23] data.table_1.10.4 SparseM_1.74 fracdiff_1.4-2 nloptr_1.0.4 rpart_4.1-10 Matrix_1.2-8 lme4_1.1-12 stringr_1.1.0 foreign_0.8-67 munsell_0.4.3 base64enc_0.1-3 [34] mgcv_1.8-17 htmltools_0.3.5 tcltk_3.3.3 nnet_7.3-12 tibble_1.2 gridExtra_2.2.1 htmlTable_1.7 quadprog_1.5-5 Hmisc_4.0-2 codetools_0.2-15 XML_3.98-1.4 [45] MASS_7.3-45 grid_3.3.3 nlme_3.1-131 jsonlite_1.1 gtable_0.2.0 magrittr_1.5 scales_0.4.1 stringi_1.1.2 timeDate_3012.100 latticeExtra_0.6-28 Formula_1.2-1 [56] RColorBrewer_1.1-2 tools_3.3.3 abind_1.4-5 parallel_3.3.3 pbkrtest_0.4-6 survival_2.40-1 colorspace_1.3-0 cluster_2.0.5 miniCRAN_0.2.7 knitr_1.15 quantreg_5.29 I have also attached the file that I used to train the model and generate forecasts. Any help will be greatly appreciated, Best regards, Paul ______________________________________________ R-help@r-project.org <mailto:R-help@r-project.org> mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help <https://stat.ethz.ch/mailman/listinfo/r-help> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html <http://www.R-project.org/posting-guide.html> and provide commented, minimal, self-contained, reproducible code.
______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
