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Time series are data observed over time (either in continuous time or at discrete time periods).
3
votes
0
answers
580
views
Double Sesonal Holt-Winters methods for data containing zeros or negative numbers
I am trying to fit dshw for the double seasonal times series, and compare the results with tbats() , I used:
> dresid.train.dshw <- dshw(dresid.ts,h = 44)
Error in dshw(dresid.ts, h = 44) :
ds …
3
votes
0
answers
613
views
How to remove the seasonality of a time series
I have got hourly data, which may have daily and annually seasonality. The ACF plot of the data are shown as follows, which is plotted up to 44 lags (upper left), 100 lags (upper right), and plot of d …
4
votes
1
answer
4k
views
Seasonal plot for time series with multiple seasonalities
My data is like the following, half hourly multi-seasonal time series from 2011 to 2016.
HH_ID Date_ID Demand Year_ID MM_ID day
201101010000 20110101 35090 2011 201101 Monday
2 …
2
votes
0
answers
300
views
Use sliding window to find variance for seasonal time series in R
I would like to estimate the variance of a time series. Say, if the time series has a period of 24, and I want to estimate the variance using
$$ \sigma_t^2 = \frac{1}{2k+1} \sum^k_{-k} (y_{t+24k} - …
6
votes
2
answers
11k
views
Missing data imputation in time series in R
I have got hourly temperature data from 2012 to 2016 as follows:
> head(htemp)
HH_ID TEMPERATURE YY_ID DD_ID MM_ID
1 201201010000 8.98 2012 20120101 201201
2 20 …
5
votes
1
answer
3k
views
How to deal with hourly non-stationary time series data with multi-seasonality?
I currently have hourly electricity demand data last for 5 years, where I used:
demand <- msts(mydata$DEMAND,seasonal.period=c(24,182.5*24,365*24),start=2012)
The plot of stl shows the data have …
11
votes
1
answer
14k
views
How to interpret TBATS model results and model diagnostics
I have got a half hourly demand data, which is a multi-seasonal time series. I used tbats in forecast package in R, and got results like this:
TBATS(1, {5,4}, 0.838, {<48,6>, <336,6>, <17520,5>})
…
2
votes
1
answer
2k
views
Time series decomposition results interpretation
I have a long multi-seasonal time series, and the stl() decomposition got me this:
The remainder is definitely not white noise. Then what should be the next step to decide the model?
Try the mode …
7
votes
2
answers
1k
views
What is the difference between ARMA+Fourier and TBATS model?
I am just wondering that, in terms of the multi-seasonal time series forecast, what is the difference between
using auto.arima find the ARMA order, then fit arima and include xreg=fourier in.
using …