Add to ORKGIn this note we analyze the relationship between one-step ahead prediction errors and interpolation errors in time series. We obtain an expression of the prediction errors in terms of the interpolation errors and then we show that minimizing the sum of squares of the one step-ahead standardized prediction errors is equivalent to minimizing the sum of squares of standardized interpolation errors
Short term time series forecasting model with different internal smoothing techniques is presented i...
The mean square error performance of simple polynomial interpolators is analyzed for wide-sense stat...
Suppose that a time series model is fitted. It is likely that the fitted model is not the true model...
In this note, we analyze the relationship between one-step ahead prediction errors and interpolation...
In this note we analyze the relationship between one-step ahead prediction errors and interpolation ...
In this note we analyze the relationship between one-step ahead prediction errors and interpolation ...
In this note we analyze the relationship between one-step ahead prediction errors and interpolation ...
In this note we analyze the relationship between one-step ahead prediction errors and interpolation ...
AbstractIt is shown that the fixed interval smoothing algorithm can be derived as a direct and simpl...
When choosing smoothing parameters in exponential smoothing, the choice can be made by either minimi...
© 2019 by the author(s). We show that classical learning methods interpolating the training data can...
© 2019 by the author(s). We show that classical learning methods interpolating the training data can...
^aThis article introduces two new types of prediction errors in time series: the filtered prediction...
^aThis article introduces two new types of prediction errors in time series: the filtered prediction...
We establish rates of convergences in statistical learning for time series forecasting. Using the PA...
Short term time series forecasting model with different internal smoothing techniques is presented i...
The mean square error performance of simple polynomial interpolators is analyzed for wide-sense stat...
Suppose that a time series model is fitted. It is likely that the fitted model is not the true model...
In this note, we analyze the relationship between one-step ahead prediction errors and interpolation...
In this note we analyze the relationship between one-step ahead prediction errors and interpolation ...
In this note we analyze the relationship between one-step ahead prediction errors and interpolation ...
In this note we analyze the relationship between one-step ahead prediction errors and interpolation ...
In this note we analyze the relationship between one-step ahead prediction errors and interpolation ...
AbstractIt is shown that the fixed interval smoothing algorithm can be derived as a direct and simpl...
When choosing smoothing parameters in exponential smoothing, the choice can be made by either minimi...
© 2019 by the author(s). We show that classical learning methods interpolating the training data can...
© 2019 by the author(s). We show that classical learning methods interpolating the training data can...
^aThis article introduces two new types of prediction errors in time series: the filtered prediction...
^aThis article introduces two new types of prediction errors in time series: the filtered prediction...
We establish rates of convergences in statistical learning for time series forecasting. Using the PA...
Short term time series forecasting model with different internal smoothing techniques is presented i...
The mean square error performance of simple polynomial interpolators is analyzed for wide-sense stat...
Suppose that a time series model is fitted. It is likely that the fitted model is not the true model...