Results 71 to 80 of about 1,212,906 (326)

Constraining the dark energy equation of state using Bayes theorem and the Kullback–Leibler divergence [PDF]

, 2016
Data-driven model-independent reconstructions of the dark energy equation of state $w(z)$ are presented using Planck 2015 era CMB, BAO, SNIa and Lyman-$\alpha$ data.
S. Hee, J. A. V'azquez, Will Handley, M. Hobson, A. Lasenby   +4 more
semanticscholar   +1 more source

Bayes Model Selection with Path Sampling: Factor Models and Other Examples

, 2013
We prove a theorem justifying the regularity conditions which are needed for Path Sampling in Factor Models. We then show that the remaining ingredient, namely, MCMC for calculating the integrand at each point in the path, may be seriously flawed ...
Dutta, Ritabrata, Ghosh, Jayanta K.
core   +1 more source

An observation‐driven state‐space model for claims size modelling

Canadian Journal of Statistics, EarlyView.
Abstract State‐space models are popular in econometrics. Recently, these models have gained some popularity in the actuarial literature. The best known state‐space models are of the Kalman‐filter type. These are called parameter‐driven because the observations do not impact the state‐space dynamics.
Jae Youn Ahn, Himchan Jeong, Mario V. Wüthrich   +2 more
wiley   +1 more source

On subset least squares estimation and prediction in vector autoregressive models with exogenous variables

Canadian Journal of Statistics, EarlyView.
Abstract We establish the consistency and the asymptotic distribution of the least squares estimators of the coefficients of a subset vector autoregressive process with exogenous variables (VARX). Using a martingale central limit theorem, we derive the asymptotic normal distribution of the estimators. Diagnostic checking is discussed using kernel‐based
Pierre Duchesne, Thanh‐Liem Huynh, Mylène Oscar   +2 more
wiley   +1 more source

Nature, Science, Bayes' Theorem, and the Whole of Reality [PDF]

, 2015
A fundamental problem in science is how to make logical inferences from scientific data. Mere data does not suffice since additional information is necessary to select a domain of models or hypotheses and thus determine the likelihood of each model or ...
Alexanian, Moorad
core  

A Markov approach to credit rating migration conditional on economic states

Canadian Journal of Statistics, EarlyView.
Abstract We develop a model for credit rating migration that accounts for the impact of economic state fluctuations on default probabilities. The joint process for the economic state and the rating is modelled as a time‐homogeneous Markov chain. While the rating process itself possesses the Markov property only under restrictive conditions, methods ...
Michael Kalkbrener, Natalie Packham
wiley   +1 more source

Probability prediction of true‐triaxial compressive strength of intact rocks based on the improved PSO‐RVM model

Deep Underground Science and Engineering, EarlyView.
In this work, we propose an improved particle swarm optimization (PSO) algorithm and develop an improved PSO‐relevance vector machine (RVM) model as a substitute for traditional true‐triaxial testing. The model's high prediction accuracy was validated through comparisons with two other machine learning methods and five three‐dimensional Hoek–Brown type
Qi Zhang, Maohui Wang, Ning Wang, Yixin Shen, Xuzhen He   +4 more
wiley   +1 more source

Bayesian Probabilities and the Histories Algebra

, 2006
We attempt a justification of a generalisation of the consistent histories programme using a notion of probability that is valid for all complete sets of history propositions.
A. Caticha, A. Caticha, C. Anastopoulos, C. J. Isham, J. B. Hartle, P. G. L. Mana, R. B. Griffiths, R. Omnés, S. Goldstein, S. Youssef, Thomas Marlow   +10 more
core   +1 more source

Artificial intelligence in preclinical epilepsy research: Current state, potential, and challenges

Epilepsia Open, EarlyView.
Abstract Preclinical translational epilepsy research uses animal models to better understand the mechanisms underlying epilepsy and its comorbidities, as well as to analyze and develop potential treatments that may mitigate this neurological disorder and its associated conditions. Artificial intelligence (AI) has emerged as a transformative tool across
Jesús Servando Medel‐Matus, Cesar Santana‐Gomez, Ruby G. Escalante, Dominique Duncan, Pedro F. Viana, Giulia Sofia Cereda, Naoto Kuroda, Aristea S. Galanopoulou   +7 more
wiley   +1 more source

Coevolutionary Algorithm with Bayes Theorem for Constrained Multiobjective Optimization

Mathematics
The effective resolution of constrained multi-objective optimization problems (CMOPs) requires a delicate balance between maximizing objectives and satisfying constraints.
Shaoyu Zhao, Heming Jia, Yongchao Li, Qian Shi   +3 more
doaj   +1 more source