Time serie visualisation and forecasting
The forecast shiny app description
This shiny application is intended to present the utility of some most popular functions from R package forecast.
It works on the time serie wineind represents Australian total wine sales by wine makers in bottles <= 1 litre. Jan 1980 – Aug 1994.
> library(forecast)
> wineind
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1980 15136 16733 20016 17708 18019 19227 22893 23739 21133 22591 26786 29740
1981 15028 17977 20008 21354 19498 22125 25817 28779 20960 22254 27392 29945
1982 16933 17892 20533 23569 22417 22084 26580 27454 24081 23451 28991 31386
1983 16896 20045 23471 21747 25621 23859 25500 30998 24475 23145 29701 34365
1984 17556 22077 25702 22214 26886 23191 27831 35406 23195 25110 30009 36242
1985 18450 21845 26488 22394 28057 25451 24872 33424 24052 28449 33533 37351
1986 19969 21701 26249 24493 24603 26485 30723 34569 26689 26157 32064 38870
1987 21337 19419 23166 28286 24570 24001 33151 24878 26804 28967 33311 40226
1988 20504 23060 23562 27562 23940 24584 34303 25517 23494 29095 32903 34379
1989 16991 21109 23740 25552 21752 20294 29009 25500 24166 26960 31222 38641
1990 14672 17543 25453 32683 22449 22316 27595 25451 25421 25288 32568 35110
1991 16052 22146 21198 19543 22084 23816 29961 26773 26635 26972 30207 38687
1992 16974 21697 24179 23757 25013 24019 30345 24488 25156 25650 30923 37240
1993 17466 19463 24352 26805 25236 24735 29356 31234 22724 28496 32857 37198
1994 13652 22784 23565 26323 23779 27549 29660 23356
In order to use personal time serie, please contact alicja.wolny-dominiak@metalitica.com.
Options
Time serie decomposition - Trend, Season, Cyclic (multiplicative and additive)
Time adapting forecasting - Exponential smoothing, Holt, Winters multiplicative, Winters additive
Forecasting with ARIMA - analysis of time serie stationarity, analysis of residual, autoarima
INTERACTIVE time serie visualisation - smoothing
Overview
Summary
Cycle
Time serie visualisation and seasons
Time serie decomposition Multiplicative: TS=T*S*R Additive: TS=T+S+R
Setting
Results
Exponential smoothing
Holt
Winters additive
Winter multiplicative
Forecast plot
Forecast results - Exponential smoothing
Accuracy measures
Forecast results - Holt
Accuracy measures
Forecast results - Winters additive
Accuracy measures
Forecast results - Winters multiplicative
Accuracy measures
CLICK HERE TO SEE ARIMA procedure manual
Stationarity, differencing, Box-Cox transformation, AR(1)=ARIMA(1,0,0) MA(1)=ARIMA(0,0,1)
Residuals
Arima forecast
mailto: alicja.wolny-dominiak@metalitica.com
author: ALicja Wolny-Dominiak, phd