Results 61 to 70 of about 1,826,552 (219)
An Effectiveness Study Of Bayesian Identification Techniques for ARMA Models [PDF]
The Egyptian Statistical Journal, 2009 Model identification is the first and most important stage when analyzing a time series. As a result of analytical complexity, very little has been done from a Bayesian viewpoint in order to identify the orders of ARMA models.
Sherif S. Ali
doaj +1 more source
Estimasi parameter model regresi multivariat bayesian dengan distribusi prior noninformatif jeffreys [PDF]
, 2018 Metode Bayesian merupakan metode yang dapat digunakan untuk meng- estimasi parameter model regresi multivariat. Dalam metode Bayesian terdapat dua distribusi yaitu distribusi prior dan posterior.
Amalia, Firda
core
A Bayes factor framework for unified parameter estimation and hypothesis testing
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract The Bayes factor, the data‐based updating factor of the prior to posterior odds of two hypotheses, is a natural measure of statistical evidence for one hypothesis over the other. We show how Bayes factors can also be used for parameter estimation.
Samuel Pawel
wiley +1 more source
Bayesian estimation of a bivariate copula using the Jeffreys prior
Bernoulli, 2012 Published in at http://dx.doi.org/10.3150/10-BEJ345 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm)
Guillotte, Simon, Perron, François
openaire +3 more sources
LLM‐based prior elicitation for Bayesian graphical modeling
British Journal of Mathematical and Statistical Psychology, EarlyView.ABSTRACT In the Bayesian graphical modeling framework, priors on network structure encode theoretical assumptions and uncertainty about the topology of psychological constructs under study. For instance, the Bernoulli prior specifies the probability of each pairwise interaction, the Beta–Bernoulli prior governs expected network density, and the ...
Nikola Sekulovski +2 more
wiley +1 more source
A Metropolis-Adjusted Langevin Algorithm for Sampling Jeffreys Prior
2025 IEEE 64th Conference on Decision and Control (CDC)Inference and estimation are fundamental in statistics, system identification, and machine learning. When prior knowledge about the system is available, Bayesian analysis provides a natural framework for encoding it through a prior distribution. In practice, such knowledge is often too vague to specify a full prior distribution, motivating the use of ...
Yibo Shi +2 more
openaire +4 more sources
To vary or not to vary: A flexible empirical Bayes factor for testing variance components
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract Random effects are the gold standard for capturing structural heterogeneity, such as individual differences or temporal dependence. Yet testing their presence is difficult because variance components are constrained to be non‐negative, creating a boundary problem. This paper introduces a flexible empirical Bayes factor (EBF) for testing random
Fabio Vieira, Hongwei Zhao, Joris Mulder
wiley +1 more source
Jeffreys noninformative prior in bayesian conjoint analysis
, 1999 컨조인트 분석은 어떤 제품이 갖고 있는 속성 하나하나에 고객이 부여하는 효용을 추정함으로써 그 고객이 어떤 제품을 선택할지를 예측하는 통계적 기법이다. 컨조인트 분석의 목표는 고객 개개인이 개별 속성의 각 수준에 대해 얼마만큼의 선호도를 부여하는지를 추정하는 데 있다. 컨조인트 모델을 분석하기 위해 무정보 사전분포인 Jeffreys 사전분포를 이용한 베이지안 분석을 적용해 보았다.
김유라
core +1 more source
Approximation of improper prior by vague priors [PDF]
, 2013 30 pages.We propose a convergence mode for prior distributions which allows a sequence of probability measures to have an improper limiting measure.
Druilhet, Pierre, Bioche, Christele
core +2 more sources
ANALISIS REGRESI BAYES LINEAR SEDERHANA DENGAN PRIOR NONINFORMATIF
E-Jurnal Matematika, 2014 The aim of this study is to apply Bayesian simple linear regression using noninformative prior. The data used in this study is 30 observational data with error generated from normal distribution.
ANAK AGUNG ISTRI AGUNG CANDRA ISWARI +2 more
doaj +1 more source