Search Results - subject:"Prediction error"

The benefit of data-based model complexity selection via prediction error curves in time-to-event data

Porzelius, Christine; Schumacher, Martin; Binder, Harald - In: Computational Statistics 26 (2011) 2, pp. 293-302

Persistent link: https://www.econbiz.de/10009149752

Accumulative prediction error as a method of model selection

Pilatowska, Mariola - In: Acta Universitatis Nicolai Copernici, Ekonomia 41 (2010), pp. 43-56

The purpose of the paper is to present and apply the accumulative one-step-ahead prediction error (APE) not only as a …

Persistent link: https://www.econbiz.de/10010610808

Comparing and generating Latin Hypercube designs in Kriging models

Pistone, Giovanni; Vicario, Grazia - In: AStA Advances in Statistical Analysis 94 (2010) 4, pp. 353-366

Persistent link: https://www.econbiz.de/10008925209

Fast robust estimation of prediction error based on resampling

Khan, Jafar A.; Van Aelst, Stefan; Zamar, Ruben H. - In: Computational Statistics & Data Analysis 54 (2010) 12, pp. 3121-3130

Robust estimators of the prediction error of a linear model are proposed. The estimators are based on the resampling … techniques cross-validation and bootstrap. The robustness of the prediction error estimators is obtained by robustly estimating …. This leads to time-efficient and robust estimators of prediction error. …

Persistent link: https://www.econbiz.de/10008864181

Forecast mean squared error reductionin the VAR(1) process

Lindstrom, J. Fredrik; Holgersson, H. E. T. - In: Journal of Applied Statistics 36 (2009) 12, pp. 1369-1384

When VAR models are used to predict future outcomes, the forecast error can be substantial. Through imposition of restrictions on the off-diagonal elements of the parameter matrix, however, the information in the process may be condensed to the marginal processes. In particular, if the...

Persistent link: https://www.econbiz.de/10008582913

Post-hoc analyses in multiple regression based on prediction error

Wilcox, Rand - In: Journal of Applied Statistics 35 (2008) 1, pp. 9-17

are found. An alternative strategy is to estimate prediction error via the 0.632 bootstrap method for all models of … interest and declare the parameters associated with the model that yields the smallest prediction error to differ from zero …

Persistent link: https://www.econbiz.de/10005458151

Calculating Confidence Intervals for Prediction Error in Microarray Classification Using Resampling

Jiang, Wenyu; Varma, Sudhir; Simon, Richard - In: Statistical Applications in Genetics and Molecular Biology 7 (2008) 1, pp. 8-8

-validation errors results in serious under-coverage of the true prediction error. Two split-sample based methods previously proposed in …

Persistent link: https://www.econbiz.de/10005246518

Nonparametric lag selection for time series

Tschernig, Rolf; Yang, Lijian - 1997

A nonparametric version of the Final Prediction Error (FPE) is proposed for lag selection in nonlinear autoregressive …

Persistent link: https://www.econbiz.de/10010310796

Nonparametric lag selection for time series

Tschernig, Rolf; Yang, Lijian - Sonderforschungsbereich 373, Quantifikation und … - 1997

A nonparametric version of the Final Prediction Error (FPE) is proposed for lag selection in nonlinear autoregressive …

Persistent link: https://www.econbiz.de/10010956477

Forecast Comparison in L2

Mizrach, Bruce - 1996

This paper provides a comprehensive framework for comparing predictors of univariate time series in the mean square norm. Initially, the forecast errors are assumed to be unbiased, independent, and normally distributed. Each of these is progressively relaxed. A new heteroscedasticity and...

Persistent link: https://www.econbiz.de/10010334303