3 votes

Forecasting using regression coefficients

Your first question: Yes, this is a valid approach. If you only want to do prediction and you think a linear dependency is appropriate, this is a valid approach. Your second question: Of course, you ...
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  • 3,153
2 votes
Accepted

Is ARIMA-GARCH nested within ARIMA?

ARIMA-GARCH is not nested within ARIMA, but ARIMA is nested within ARIMA-GARCH. This is because you can obtain ARIMA from ARIMA-GARCH by simplifying the latter model's conditional variance equation to ...
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1 vote

Cross Validation for Time Series Classification (Not Forecasting!)

There is no problem with using K-fold cross-validation using the entire time series in time series classification. It is commonly used with algorithms such as NN-DTW (Nearest Neighbour Dynamic Time ...
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  • 543
1 vote

Using weather forecasts as exogenous data for timeseries forecasting

It's a good question. I would try both and see what happens. It also kinda depends on the thing you are forecasting, for example trips to disney world may depend more on the lagged weather forecast as ...
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  • 1,275
1 vote

Using weather forecasts as exogenous data for timeseries forecasting

I'd definitely go with your option (1). Here's a couple of reasons why: It's possible that the weather forecasts will show a (hopefully small) bias by D-4. Then option (2) would result in biased ...
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  • 16.9k
1 vote

Shall I use daily or monthly data for demand forecasting?

It all depends very much on what you plan on doing with your forecast. If you use it for production planning, and your production plans are always frozen in monthly buckets, then you need a forecast ...
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1 vote
Accepted

Forecasting based on few samples

Your data can be plotted as follows: Note: Always plot your data! Especially if you want to forecast. In covid models, a V-shape recovery has been quite frequent. The blue line is your data. The red ...
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1 vote

time series forecasting model cannot beat baseline

You didn't give us many details about your data, but if you don't have many observations then the simple methods like predicting the previous value work remarkably well. What is the frequency of your ...
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  • 113k
1 vote

Generalized Linear Models vs Timseries models for forecasting

I myself was studying neural behavior a long time and I must say that GLMs did a really good job in predicting the complex neural behavior based on external factors but also the activity of other ...
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  • 230

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