3. Fitting a regression model of the series on a periodic function (e.g. sine wave of a fixed period) of the time index and subtracting off the fitted model from the series. What could this method achieve? (Choose all that apply.) remove a linear trend remove a nonlinear trend remove increasing variance remove seasonal variation 4. Differencing the data one or more times. What could this method achieve? (Choose all that apply.) remove a linear trend remove a nonlinear trend remove increasing variance remove seasonal variation

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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Consider the following techniques of transforming time series data. Choose all that apply

3. Fitting a regression model of the series on a periodic function (e.g. sine wave of a fixed period) of the time index and
subtracting off the fitted model from the series.
What could this method achieve? (Choose all that apply.)
remove a linear trend
remove a nonlinear trend
remove increasing variance
remove seasonal variation
4. Differencing the data one or more times.
What could this method achieve? (Choose all that apply.)
remove a linear trend
remove a nonlinear trend
remove increasing variance
remove seasonal variation
Transcribed Image Text:3. Fitting a regression model of the series on a periodic function (e.g. sine wave of a fixed period) of the time index and subtracting off the fitted model from the series. What could this method achieve? (Choose all that apply.) remove a linear trend remove a nonlinear trend remove increasing variance remove seasonal variation 4. Differencing the data one or more times. What could this method achieve? (Choose all that apply.) remove a linear trend remove a nonlinear trend remove increasing variance remove seasonal variation
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