نتایج جستجو برای: bayesian factor analysis

تعداد نتایج: 3529139  

2014
Shiwen Zhao Chuan Gao Sayan Mukherjee Barbara E Engelhardt

Latent factor models are the canonical statistical tool for exploratory analyses of lowdimensional linear structure for an observation matrix with p features across n samples. We develop a Bayesian group factor analysis (BGFA) model that extends the factor model to multiple coupled observation matrices. Our model puts a structured Bayesian hierarchical prior on the joint factor loading matrix, ...

2014
Shiwen Zhao Chuan Gao Sayan Mukherjee Barbara E Engelhardt

Latent factor models are the canonical statistical tool for exploratory analyses of lowdimensional linear structure for an observation matrix with p features across n samples. We develop a Bayesian group factor analysis (BGFA) model that extends the factor model to multiple coupled observation matrices. Our model puts a structured Bayesian hierarchical prior on the joint factor loading matrix, ...

The present paper introduces the Bayesian spectral analysis as a powerful and efficient method for spectral analysis of photometric time series. For this purpose, Bayesian spectral analysis has programmed in Matlab software for XZ Dra photometric time series which is non-uniform with large gaps and the power spectrum of this analysis has compared with the power spectrum which obtained from the ...

Journal: :The British journal of mathematical and statistical psychology 2001
X Y Song S Y Lee

The main purpose of this paper is to develop a Bayesian approach for the multisample factor analysis model with continuous and polytomous variables. Joint Bayesian estimates of the thresholds, the factor scores and the structural parameters subjected to some simple constraints across groups are obtained simultaneously. The Gibbs sampler is used to produce the joint Bayesian estimates. It is sho...

ژورنال: علوم آب و خاک 2022

Proper flood discharge forecasting is significant for the design of hydraulic structures, reducing the risk of failure, and minimizing downstream environmental damage. The objective of this study was to investigate the application of machine learning methods in Regional Flood Frequency Analysis (RFFA). To achieve this goal, 18 physiographic, climatic, lithological, and land use parameters were ...

Journal: :international journal of environmental research 2010
a.h. ehsani f. quiel

two different methods of bayesian segmentation algorithm were used with different band combinations. sequential maximum a posteriori (smap) is a bayesian image segmentation algorithm which unlike the traditional maximum likelihood (ml) classification attempts to improve accuracy by taking contextual information into account, rather than classifying pixels separately. landsat 7 etm+ data with pa...

ژورنال: طب کار 2014
حلوانی, غلامحسین , زارع سخویدی, محمدجواد, سموری, فاطمه, فلاح زاده, حسین , مستغاثی, مهرداد, میهن پور, حمیده,

Background: expert judgments in combination with exposure models are used extensively in estimation of inhalational exposures in occupational environments. However, their reliability is not as good as conventional air sampling methods. The aim of this study was to investigate the applicability, weaknesses and strengths of Bayesian analysis in combination with SSA (Structured Subjective Assessme...

2005
HIROTUGU AKAIKE

The information criterion AIC was introduced to extend the method of maximum likelihood to the multimodel situation. It was obtained by relating the successful experience of the order determination of an autoregressive model to the determination of the number of factors in the maximum likelihood factor analysis. The use of the AIC criterion in the factor analysis is particularly interesting whe...

In risk analysis based on Bayesian framework, premium calculation requires specification of a prior distribution for the risk parameter in the heterogeneous portfolio. When the prior knowledge is vague, the E-Bayesian and robust Bayesian analysis can be used to handle the uncertainty in specifying the prior distribution by considering a class of priors instead of a single prior. In th...

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