The Bayesian estimator based on these algorithms can account for the selection bias and the full covariance structure implied by the spatial correlation. We illustrate the implementation of these algorithms through a simulation study.doi:10.1111/obes.12187Dogan, OsmanTaspinar, SuleymanUniversity Library of Munich, GermanyMPRA Paper
method that is used to make statistical inference.Only one value is allowed. Posterior distribution characterization is the default setting (ANALYSIS = POSTERIOR). WhenANALYSIS = BAYESFACTOR, only the Bayes-factor estimation procedure is invoked. WhenANALYSIS = BOTH, both of the procedures are used...
R. Merlin—rapid analysis of dense genetic maps using sparse gene flow trees. Nat. Genet. 30, 97–101 (2002). Article CAS Google Scholar de Villemereuil, P., Schielzeth, H., Nakagawa, S. & Morrissey, M. General methods for evolutionary quantitative genetic inference from generalized ...
Using Bayesian multilevel regression, we find that on average, word-initial consonants are about 13 ms longer than word-medial consonants. The cross-linguistic distribution of the effect indicates that despite individual differences in the phonology of the sampled languages, the lengthening of word...
Predictive inference usually involves the derivation of a probability model of future responses given an informative data set. From the predictive model, one may infer the future characteristics of a model such as the mean, standard deviation, tolerance region, etc. The Bayesian method is widely ...
M. (1997), Statistical inference as a decision problem: the choice of sample size, The Statistician 46, 151-153.Bernardo, J. M. (1997). Statistical inference as a decision problem: The choice of sample size. The Statistician 46, 151-153....
In most human societies, there are taboos and laws banning mating between first- and second-degree relatives, but actual prevalence and effects on health and fitness are poorly quantified. Here, we leverage a large observational study of ~450,000 partici
Specifically, the approach of the former authors is based on Markov chain Monte Carlo simulation techniques and uses a simultaneous equation system that incorporates Bayesian versions of penalized smoothing splines. The latter further extended this approach by introducing a Bayesian algorithm based on low...
Bayesian Inference for Nonlinear and Non-Gaussian Stochastic Volatility Model with Leverage Effect Stochastic volatility (SV) models provide useful tools to describe the evolution of asset returns, which exhibit time-varying volatility. This paper extend... T Ando - 《Journal of the Japan Statistical...
BASS performs multi-scale transcriptomic analyses in the form of joint cell type clustering and spatial domain detection, with the two analytic tasks carried out simultaneously within a Bayesian hierarchical modeling framework. For both analyses, BASS properly accounts for the spatial correlation structure...