Results 71 to 80 of about 1,212,947 (298)
Dynamics, 2023 In the cognitive and neural sciences, Bayesianism refers to a collection of concepts and methods stemming from various implementations of Bayes’ theorem, which is a formal way to calculate the conditional probability of a hypothesis being true based on ...
Luis H. Favela, Mary Jean Amon
doaj +1 more source
BAT - The Bayesian Analysis Toolkit
, 2008 We describe the development of a new toolkit for data analysis. The analysis package is based on Bayes' Theorem, and is realized with the use of Markov Chain Monte Carlo. This gives access to the full posterior probability distribution.
Akaike +14 more
core +1 more source
Predicting cervical cancer DNA methylation from genetic data using multivariate CMMP
Canadian Journal of Statistics, EarlyView.Abstract Epigenetic modifications link the environment to gene expression and play a crucial role in tumour development. DNA methylation, in particular, is gaining attention in cancer research, including cervical cancer, the focus of this study.
Hang Zhang +5 more
wiley +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
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 +4 more
semanticscholar +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 +2 more
wiley +1 more source
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 +2 more
wiley +1 more source
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
The Sky Has Its Limits in COVID-19 Testing
Rambam Maimonides Medical Journal, 2020 At the time of writing, in July 2020, the COVID-19 pandemic has already inflicted dramatic international restrictions, including airports closing and limiting international travel. It has been suggested that re-opening of airports should involve and even
Shai Lin, Shay Tzafrir, Shay Gueron
doaj +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