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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 …
Luca Thiede's user avatar
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 \ …
Luca Thiede's user avatar
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 …
Luca Thiede's user avatar
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 …
Luca Thiede's user avatar
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 …
Luca Thiede's user avatar