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kjetil b halvorsen ♦
kjetil b halvorsen ♦
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I am using a time series for monthly temperatures to predict future temperatures.

To this I am using the seasonal ARIMA model and Holt Winters forecast, and my results seems fine.

However, my data set shows that the variance depends on the month. In the winter the temperature changes a lot more over the years than in the summer.

Can I do anything to even out the variance and is iit necessary to use SARIMA and HW i R?

I am using a time series for monthly temperatures to predict future temperatures.

To this I am using the seasonal ARIMA model and Holt Winters forecast, and my results seems fine.

However, my data set shows that the variance depends on the month. In the winter the temperature changes a lot more over the years than in the summer.

Can I do anything to even out the variance and is i necessary to use SARIMA and HW i R?

I am using a time series for monthly temperatures to predict future temperatures.

To this I am using the seasonal ARIMA model and Holt Winters forecast, and my results seems fine.

However, my data set shows that the variance depends on the month. In the winter the temperature changes a lot more over the years than in the summer.

Can I do anything to even out the variance and is it necessary to use SARIMA and HW i R?

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Skovbaek
Skovbaek
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Variance inhomogeneity in time series when forecasting

I am using a time series for monthly temperatures to predict future temperatures.

To this I am using the seasonal ARIMA model and Holt Winters forecast, and my results seems fine.

However, my data set shows that the variance depends on the month. In the winter the temperature changes a lot more over the years than in the summer.

Can I do anything to even out the variance and is i necessary to use SARIMA and HW i R?