共查询到20条相似文献,搜索用时 15 毫秒
1.
Joachim Schütze 《Allgemeines Statistisches Archiv》2005,89(2):237-240
Literatur / Books
Buchbesprechungen / Book reviews 相似文献2.
Norman Fickel G?tz Uebe Karsten Webel Benedikt K?hler 《Allgemeines Statistisches Archiv》2004,88(3):368-374
Buchbesprechungen / Book reviews
Literatur / Books 相似文献3.
Buchbesprechungen / Book reviews
Literatur / Books 相似文献4.
《Allgemeines Statistisches Archiv》2005,89(1):98-105
Literatur / Books
Buchbesprechungen / Book reviews 相似文献5.
Norman Fickel G?tz Uebe Karsten Webel Benedikt K?hler 《Allgemeines Statistisches Archiv》2005,89(4):469-477
Literatur / Books
Buchbesprechungen / Book reviews 相似文献6.
N. Lack 《Allgemeines Statistisches Archiv》2004,88(4):487-488
Rundschau / News &; Reports
Danksagung 相似文献7.
Jean-Jacques Strodiot Jean-Pierre Crouzeix Jacques A. Ferland Van Hien Nguyen 《Statistical Papers》2011,52(1):255-256
Problem Section
Solution of problem 5/SP08: a birth–death process with polynomial transitions Proposed by Randall J. Swift, California State Polytechnic University, Pomona, USA 相似文献8.
Improvement of the Liu estimator in linear regression model 总被引:2,自引:0,他引:2
In the presence of stochastic prior information, in addition to the sample, Theil and Goldberger (1961) introduced a Mixed
Estimator
for the parameter vector β in the standard multiple linear regression model (T,Xβ,σ2
I). Recently, the Liu estimator which is an alternative biased estimator for β has been proposed by Liu (1993).
In this paper we introduce another new Liu type biased estimator called Stochastic restricted Liu estimator
for β, and discuss its efficiency. The necessary and sufficient conditions for mean squared error matrix of the Stochastic restricted Liu estimator
to exceed the mean squared error matrix of the mixed estimator
will be derived for the two cases in which the parametric restrictions are correct and are not correct. In particular we
show that this new biased estimator is superior in the mean squared error matrix sense to both the Mixed estimator
and to the biased estimator introduced by Liu (1993). 相似文献
9.
10.
Call for Papers
International Conference on "Statistical Latent Variables Models in the Health Sciences" 相似文献11.
Erratum
Testing equality of cause-specific hazard rates corresponding to m competing risks among K groups 相似文献12.
13.
A. P. Dawid 《Statistics and Computing》1992,2(1):25-36
A probabilistic expert system provides a graphical representation of a joint probability distribution which can be used to simplify and localize calculations. Jensenet al. (1990) introduced a flow-propagation algorithm for calculating marginal and conditional distributions in such a system. This paper analyses that algorithm in detail, and shows how it can be modified to perform other tasks, including maximization of the joint density and simultaneous fast retraction of evidence entered on several variables. 相似文献
14.
15.
Radford M. Neal 《Statistics and Computing》1996,6(4):353-366
I present a new Markov chain sampling method appropriate for distributions with isolated modes. Like the recently developed method of simulated tempering, the tempered transition method uses a series of distributions that interpolate between the distribution of interest and a distribution for which sampling is easier. The new method has the advantage that it does not require approximate values for the normalizing constants of these distributions, which are needed for simulated tempering, and can be tedious to estimate. Simulated tempering performs a random walk along the series of distributions used. In contrast, the tempered transitions of the new method move systematically from the desired distribution, to the easily-sampled distribution, and back to the desired distribution. This systematic movement avoids the inefficiency of a random walk, an advantage that is unfortunately cancelled by an increase in the number of interpolating distributions required. Because of this, the sampling efficiency of the tempered transition method in simple problems is similar to that of simulated tempering. On more complex distributions, however, simulated tempering and tempered transitions may perform differently. Which is better depends on the ways in which the interpolating distributions are deceptive. 相似文献
16.
Marten H. Wegkamp 《Revue canadienne de statistique》1999,27(2):409-420
Let f?n, h denote the kernel density estimate based on a sample of size n drawn from an unknown density f. Using techniques from L2 projection density estimators, the author shows how to construct a data-driven estimator f?n, h which satisfies This paper is inspired by work of Stone (1984), Devroye and Lugosi (1996) and Birge and Massart (1997). 相似文献
17.
18.
Stephen Rowe 《Statistics and Computing》1996,6(3):187-190
In Flury (1990) the k principal points of a random vector X are defned as the points p(1),..., p(k) minimizing EX–p(i)2; i=1,..., k. We extend this concept to that of k principal points with respect to a loss function L, and present an algorithm for their computation in the univariate case. 相似文献
19.
Convergence assessment techniques for Markov chain Monte Carlo 总被引:7,自引:0,他引:7
MCMC methods have effectively revolutionised the field of Bayesian statistics over the past few years. Such methods provide invaluable tools to overcome problems with analytic intractability inherent in adopting the Bayesian approach to statistical modelling.However, any inference based upon MCMC output relies critically upon the assumption that the Markov chain being simulated has achieved a steady state or converged. Many techniques have been developed for trying to determine whether or not a particular Markov chain has converged, and this paper aims to review these methods with an emphasis on the mathematics underpinning these techniques, in an attempt to summarise the current state-of-play for convergence assessment techniques and to motivate directions for future research in this area. 相似文献
20.
《The American statistician》2012,66(4):327-339
ABSTRACTWith an increasing number of replication studies performed in psychological science, the question of how to evaluate the outcome of a replication attempt deserves careful consideration. Bayesian approaches allow to incorporate uncertainty and prior information into the analysis of the replication attempt by their design. The Replication Bayes factor, introduced by Verhagen and Wagenmakers (2014), provides quantitative, relative evidence in favor or against a successful replication. In previous work by Verhagen and Wagenmakers (2014), it was limited to the case of t-tests. In this article, the Replication Bayes factor is extended to F-tests in multigroup, fixed-effect ANOVA designs. Simulations and examples are presented to facilitate the understanding and to demonstrate the usefulness of this approach. Finally, the Replication Bayes factor is compared to other Bayesian and frequentist approaches and discussed in the context of replication attempts. R code to calculate Replication Bayes factors and to reproduce the examples in the article is available at https://osf.io/jv39h/. 相似文献