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Results tagged with Search options user 2407

Time series are data observed over time (either in continuous time or at discrete time periods).

1
vote
1answer
The short question: Are there any studies of systems described by several hidden stochastic time dependent variables and observed variables that are given by known deterministic functions of hidden v …
asked Mar 11 '13 by Roman
4
votes
2answers
Assume that we have a time series and we have calculate the corresponding auto-covariance function. Having the auto-covariance function we can calculate the corresponding power spectrum and having the …
asked Oct 28 '14 by Roman
1
vote
The short answer: to evaluate the quality of your predictions, use exactly the same measure that you used in the training (fitting) of your model. The long answer: In order to chose a measure for th …
answered Sep 17 '14 by Roman
1
vote
0answers
In ARMA model we postulate that predictions of time series can be calculated as a linear function of $N$ previous observations (AR part) and $K$ differences between the previous observations and the c …
asked Dec 2 '15 by Roman
10
votes
2answers
The idea behind Recurrent Neural Network (RNN) is clear to me. I understand it in the following way:We have a sequence of observations ($\vec o_1, \vec o_2, \dots, \vec o_n$) (or, in other words, mult …
asked Apr 5 '16 by Roman
1
vote
2answers
In this paper I saw the following statement: If the time series is Gaussian (i.e., normally distributed) then the best linear forecast is in fact the best of all possible forecasts: No nonline …
asked Dec 2 '15 by Roman