CODEWITHSUNDEEP
rtimetime-seriesforecastingarima
Sandy123
Sandy123

Reputation: 1

time series analysis in R (short term forecasting through daily data)

I am working in R, I need to ask that I have daily data for almost 11 months for every minute e.g

Date_Time  Usage_kW
0:00        1.7382
0.01        1.7892
0.02        1.7125
....          .
...           .
....          .
1.00          .
.             .
.       .
.

so on

and cycle repeats after every 60 minutes, so I chose the frequency 60 but I am not able to get the best prediction through arima model as the data is nonseasonal, please help me in selecting the correct value for frequency=?, start=? and end=? values

mydata<-ts(Usage[,2], start=1, end=24, frequency=60)

I want to plot data on daily basis e.g 24 hours??

Upvotes: 0

Views: 220

Answers (1)

Zeeshan
Zeeshan

Reputation: 1238

you should merge the every minute data into either hour or daily or weekly then check accuracy of ARIMA model. You can also try other Forecasting methodes also like SMA,WMA,Holt Winter,tbats,Prophet,etc.. and select the model which is giving good accuracy(MAPE).

Update:

Once the frequency of observations is smaller than a week, then there is usually more than one way of handling the frequency. For example, data observed every minute might have an hourly seasonality (frequency=60), a daily seasonality (frequency=24x60=1440), a weekly seasonality (frequency=24x60x7=10080) and an annual seasonality (frequency=24x60x365.25=525960). If you want to use a ts object, then you need to decide which of these is the most important.

Upvotes: 1

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