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To begin with sometimes outliers are present when the series is high incorrectly suggesting a box-cox transformation. Transformations ala box -coxhttp://stats.stackexchange.com/questions/18844/when-an …

Iterate to a minimally sufficient model incorporating as necessary ARMA structure and deterministic structure. . How to evaluate deterministic vs stochastic components of a time series? . In my experi …

I don't think that it makes that much difference as to which method you use . The only way I could find out would be to measure ultimate model accuracy to determine a winner. What does matter is what …

Series Y is visually non-stationary . Two useful remedies for non-stationarity are to either difference the data or to incorporate level shift indicators i.e. to demean . In my opinion ( without havin …

1.5.2.1 is an attempt to obtain an equally weighted (except for the two endpoints) central average over 2 seasons (not 3 or 4 or any other ) thus obtaining a centralized replacement value that is supp …

yt=δ+yt−1+ϵt is the leftmost plot while yt=β0+β1t+ϵt is the rightmost plot. Both original time series have very similar acf's and pacf's thus model identification is difficult as the two competing mod …

you have 9 data points per series. Time series data can have either deterministic trends (the one you are probably referring to ) or stochastic trends ... see stochastic vs. deterministic trend in tim …

For each of the m countries, one could predict the next k years and compute the uncertainty in those k predictions. Compute the relative "volatility" by converting the forecast standard deviation ( or …

Let us review the assumptions that are made when it is safe to visually or computationally map the sample acf and pacf to a useful arima model. Firstly there must be no deterministic structure latent …

If you are correctly incorporating day-of-the-week, day-of-the month, month, quarter, lead & contemporaneous & lag holiday effects and step/level shifts and local time trends AND accommodating one-tim …

You can build a model at the hourly level and forecast the next N hours for the next K days If there are hidden/latent anthropormorphic effects such as day-of-the-week effects , day-of-the-month eff …

Use the Ljung-Box test https://en.wikipedia.org/wiki/Ljung%E2%80%93Box_test to test the autocorrelations. If there are significant autocorrelations you might investigate the following 1) add structu …

I believe that you are trying to use statistical methods that are appropriate for independent observations while you have correlated data, both temporarily and spatially. If you have observations say …

You have time series data and one develops an equation for intra-day usage which may use either an auto-projective ARIMA model or a set of fixed dummies (23 in number) to predict hourly expectations. …

Patrick, You could add a series 0,0,0,0,0,....1,1,1,1,1,1,1,1,1,1,1,1, ,0,0,0,0, where the 1's reflect the year you are trying to test. This variable would be the X variable in an ARMAX model and it …