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Time series are data observed over time (either in continuous time or at discrete time periods).
1
vote
0
answers
149
views
Problem with features in time series classification
For a student project, we got data like this:
A one dimensional time series
A classification label
Two further features/parameters, unrelated to the time series
At the end of the time series there …
5
votes
1
answer
5k
views
Why is a GARCH model useful?
As I understand it, one can model changing variance of a time series process with a GARCH model. What I don't understand is, how can one actually make predictions with this?
Since
$$
y_t = \sigma_t \ …
2
votes
1
answer
214
views
Stationarity of MA($\infty$) process
In my time series class, we got taught, that an MA($\infty $) process with
$$
\sum_i^\infty \theta_i^2 < \infty
$$
is weakly stationary.
Obviously the mean exists and is time independent, but why d …
6
votes
1
answer
1k
views
Under which assumptions does weak stationarity imply strong stationarity
An excercise question for time series analysis asks:
Consider the process
$$
y_t = 0.8y_{t-1} + 0.1y_{t-2} + u_t
$$
Is this process weakly stationary (I would answer this with the stability triangl …
5
votes
1
answer
2k
views
Fitting MA(q) and ARIMA(q) model
I know, that fitting an AR(q) model can easily be done by OLS.
Now I wonder, how to do it for MA(q) and ARIMA(p,q), but cant find enything useful, except, that one uses Maximum Likelihood and needs m …