Titlebook: Contemporary Developments in Statistical Theory; A Festschrift for Hi Soumendra Lahiri,Anton Schick,T.N. Sriram Conference proceedings 2014

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Comparison of Autoregressive Curves Through Partial Sums of Quasi-Residuals,dastic error and stationary densities of the two independent strong mixing strictly stationary time series can be possibly different. The chapter adapts the partial sum process idea used in the independent observations settings to construct the tests and derives their asymptotics under both null and

Meditative

Testing for Long Memory Using Penalized Splines and Adaptive Neyman Methods,ing penalized splines method and Fan’s (.) canonical multivariate normal hypothesis testing procedure. Using penalized splines method, we are able to eliminate the effects of nuisance parameters typically induced by short memory autocorrelation. Therefore, under the null hypothesis of any short memo

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How to Choose the Number of Gradient Directions for Estimation Problems from Noisy Diffusion Tensorce between the number of distinct directions for measurements and the number of repetitions is investigated from the statistical point of view. We show that designs with multiple independent repetitions using one set of six directions for the low resolution case yield smaller norms of the estimator’

Working-Memory

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Springer Proceedings in Mathematics & Statisticshttp://image.papertrans.cn/c/image/236442.jpg

FOLLY

Frank Huber,Isabel Matthes,Nadine Stennekenel. He has the unique distinction of being the first doctoral student of Professor Bickel. True to his training at Berkeley, in the initial years of his research career, he focused on developing asymptotic theory of statistical inference. He pioneered the approach of . (AUL) as a theoretical tool fo

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Frank Huber,Isabel Matthes,Nadine Stennekenesults on asymptotic op¬timality of the estimates are discussed for both ergodic and non-ergodic processes. To illustrate the main results, various parameter estimates for GARCH-type processes, bifur¬cating and explosive autoregressive processes, conditionally linear autoregressive processes, and br

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