In 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
This paper brings together two topics in the estimation of time series forecasting models: the use o...
Historical time series sometimes have missing observations. It is common practice either to ignore t...
We study the fitting of time series models via the minimization of a multi-step-ahead forecast error...
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 ...
A thorough review has been performed on interpolation methods to fill gaps in time-series, efficienc...
A thorough review has been performed on interpolation methods to fill gaps in time-series, efficienc...
A thorough review has been performed on interpolation methods to fill gaps in time-series, efficienc...
A thorough review has been performed on interpolation methods to fill gaps in time-series, efficienc...
^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...
Prediction accuracy of the response variable at future time points in a time series is a function of...
This paper brings together two topics in the estimation of time series forecasting models: the use o...
Historical time series sometimes have missing observations. It is common practice either to ignore t...
We study the fitting of time series models via the minimization of a multi-step-ahead forecast error...
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 ...
A thorough review has been performed on interpolation methods to fill gaps in time-series, efficienc...
A thorough review has been performed on interpolation methods to fill gaps in time-series, efficienc...
A thorough review has been performed on interpolation methods to fill gaps in time-series, efficienc...
A thorough review has been performed on interpolation methods to fill gaps in time-series, efficienc...
^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...
Prediction accuracy of the response variable at future time points in a time series is a function of...
This paper brings together two topics in the estimation of time series forecasting models: the use o...
Historical time series sometimes have missing observations. It is common practice either to ignore t...
We study the fitting of time series models via the minimization of a multi-step-ahead forecast error...
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