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
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