نتایج جستجو برای: based inferences relying on our sampling

تعداد نتایج: 9711349  

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه اراک - دانشکده علوم انسانی 1389

this study investigates the cohesive devices used in the textbook of english for the students of psychology. the research questions and hypotheses in the present study are based on what frequency and distribution of grammatical and lexical cohesive devices are. then, to answer the questions all grammatical and lexical cohesive devices in reading comprehension passages from 6 units of 21units th...

پایان نامه :دانشگاه آزاد اسلامی - دانشگاه آزاد اسلامی واحد تهران مرکزی - دانشکده زبانهای خارجی 1393

the purpose of this study was to examine the comparative effect of story retelling and role playing on efl learners’ vocabulary learning and reading comprehension. to carry out the purpose of the study 90 female learners of tabarestan language school located in noshahr were non-randomly selected. they took pet test and among these 90 participants 62 students were selected as homogenous learners...

2016
Loh Yue Fang Jayanthi Arasan Mohd Rizam Abu Bakar

Traditional inferential procedures based on the asymptotic normality assumption such as the Wald often produce misleading inferences when dealing with censored data and small samples. Alternative estimation techniques such as the jackknife and bootstrap percentile allow us to construct the interval estimates without relying on any classical assumptions. Recently, the double bootstrap became pre...

2010
Shirley J. Huang Jun Yu

In this paper a Markov chain Monte Carlo (MCMC) technique is developed for the Bayesian analysis of structural credit risk models with microstructure noises. The technique is based on the general Bayesian approach with posterior computations performed by Gibbs sampling. Simulations from the Markov chain, whose stationary distribution converges to the posterior distribution, enable exact finite ...

Journal: :IEEE Transactions on Vehicular Technology 2022

The security aspects of aeronautical ad-hoc networks (AANET) relying on reflective intelligent surface (RIS) are considered. A projection-based deep neural network (DNN) is designed for maximizing the secrecy rate proposed RIS-aided AANET. While multiple-layer architecture DNN enables learning ...

2011
Florian Kutzner Tobias Vogel Peter Freytag Klaus Fiedler

Fiedler et al. (2009), reviewed evidence for the utilization of a contingency inference strategy termed pseudocontingencies (PCs). In PCs, the more frequent levels (and, by implication, the less frequent levels) are assumed to be associated. PCs have been obtained using a wide range of task settings and dependent measures. Yet, the readiness with which decision makers rely on PCs is poorly unde...

Journal: :American journal of botany 2015
Carl J Rothfels Fay-Wei Li Erin M Sigel Layne Huiet Anders Larsson Dylan O Burge Markus Ruhsam Michael Deyholos Douglas E Soltis C Neal Stewart Shane W Shaw Lisa Pokorny Tao Chen Claude dePamphilis Lisa DeGironimo Li Chen Xiaofeng Wei Xiao Sun Petra Korall Dennis W Stevenson Sean W Graham Gane K-S Wong Kathleen M Pryer

UNLABELLED • PREMISE OF THE STUDY Understanding fern (monilophyte) phylogeny and its evolutionary timescale is critical for broad investigations of the evolution of land plants, and for providing the point of comparison necessary for studying the evolution of the fern sister group, seed plants. Molecular phylogenetic investigations have revolutionized our understanding of fern phylogeny, howe...

1999
Tim C Hesterberg

We propose a bootstrap sampling method jackboot sampling This provides more accu rate inferences than ordinary bootstrap sampling better con dence interval coverage and less biased or unbiased standard errors The method is simple to implement We also prescribe a smoothing parameter for use in smoothed bootstrapping using or dinary kernel smoothing The e ect is similar to that of jackboot sampling

2017
Ioannis Mitliagkas Lester W. Mackey

The pairwise influence matrix of Dobrushin has long been used as an analytical tool to bound the rate of convergence of Gibbs sampling. In this work, we use Dobrushin influence as the basis of a practical tool to certify and efficiently improve the quality of a Gibbs sampler. Our Dobrushin-optimized Gibbs samplers (DoGS) offer customized variable selection orders for a given sampling budget and...

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