On selection of prior distribution in inverse analyses by Akaike Bayesian Information Criterion
نویسندگان
چکیده
منابع مشابه
An improved Akaike information criterion for state-space model selection
Following the work of Hurvich, Shumway, and Tsai (1990), we propose an “improved” variant of the Akaike information criterion, AICi, for state-space model selection. The variant is based on Akaike’s (1973) objective of estimating the Kullback-Leibler information (Kullback 1968) between the densities corresponding to the fitted model and the generating or true model. The development of AICi proc...
متن کاملPrior Model Selection for Bayesian Inverse Electrocardiography
The goal of the inverse problem of electrocardiography (ECG) is to reconstruct cardiac electrical sources using body surface potential measurements, and an appropriate mathematical model representing the thorax [1,2]. However, due to attenuation and smoothing that occurs in the thorax, the problem is ill-posed and reliable solutions require regularization. The application of suitable regulariza...
متن کاملModel selection and model averaging in phylogenetics: advantages of akaike information criterion and bayesian approaches over likelihood ratio tests.
Model selection is a topic of special relevance in molecular phylogenetics that affects many, if not all, stages of phylogenetic inference. Here we discuss some fundamental concepts and techniques of model selection in the context of phylogenetics. We start by reviewing different aspects of the selection of substitution models in phylogenetics from a theoretical, philosophical and practical poi...
متن کاملExponential Smoothing and the Akaike Information Criterion
Using an innovations state space approach, it has been found that the Akaike information criterion (AIC) works slightly better, on average, than prediction validation on withheld data, for choosing between the various common methods of exponential smoothing for forecasting. There is, however, a puzzle. Should the count of the seed states be incorporated into the penalty term in the AIC formula?...
متن کاملA Bayesian information criterion for portfolio selection
The mean-variance theory of Markowitz (1952) indicates that large investment portfolios naturally provide better risk diversification than small ones. However, due to parameter estimation errors, one may find ambiguous results in practice. Hence, it is essential to identify relevant stocks to alleviate the impact of estimation error in portfolio selection. To this end, we propose a linkage cond...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of applied mechanics
سال: 2004
ISSN: 1345-9139,1884-832X
DOI: 10.2208/journalam.7.145