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Testing diffusion processes for non-stationarity

Hamrick, Jeff; Taqqu, Murad - In: Computational Statistics 69 (2009) 3, pp. 509-551

Hochberg (J R Stat Soc Ser B, 59:289–300, 1995), we develop a test for non-stationarity of a one-dimensional diffusion based on …

Persistent link: https://www.econbiz.de/10010759501

Bootstrap prediction intervals in beta regressions

Espinheira, Patrícia; Ferrari, Silvia; Cribari-Neto, … - In: Computational Statistics 29 (2014) 5, pp. 1263-1277

We address the issue of constructing prediction intervals for responses that assume values in the standard unit …> </EquationSource> </InlineEquation> (bias-corrected and accelerated) bootstrap prediction intervals. We present Monte Carlo evidence on …

Persistent link: https://www.econbiz.de/10010998523

Comparisons among some predictors of exponential distributions using Pitman closeness

Raqab, Mohammad; Ahmadi, Jafar; Arabli, Byan - In: Computational Statistics 28 (2013) 5, pp. 2349-2365

The bias, mean squared error and likelihood optimality criteria are used frequently to compare estimators and predictors. Recently, the probability of nearness around a statistic (estimator or predictor) has received a considerable attention in the literature. In this article, we adopt the...

Persistent link: https://www.econbiz.de/10010847470

On-line portfolio selection strategy with prediction in the presence of transaction costs

Albeverio, Sergio; Lao, LanJun; Zhao, XueLei - In: Computational Statistics 54 (2001) 1, pp. 133-161

the same exponential growth rate of wealth as the best stock for a long term. This equipped with a new prediction method …

Persistent link: https://www.econbiz.de/10010847671

Empirical properties of forecasts with the functional autoregressive model

Didericksen, Devin; Kokoszka, Piotr; Zhang, Xi - In: Computational Statistics 27 (2012) 2, pp. 285-298

Persistent link: https://www.econbiz.de/10010847795

Prediction interval for disease mapping using hierarchical likelihood

Lee, Youngjo; Jang, Myoungjin; Lee, Woojoo - In: Computational Statistics 26 (2011) 1, pp. 159-179

Persistent link: https://www.econbiz.de/10008925416

Variable selection after screening: with or without data splitting?

Zhu, Xiaoyi; Yang, Yuhong - In: Computational Statistics 30 (2015) 1, pp. 191-203

final selection of a number of predictors that have no/little value for prediction/explanation. In this paper we set to … screening bias for variable selection and improve the prediction accuracy as well. Copyright Springer-Verlag Berlin Heidelberg …

Persistent link: https://www.econbiz.de/10011241311