In particular, when the response variable y t in a regression model is a binary variable that only takes the values 0 and 1, a natural extension of the linear regression function 胃 T x t is to relate how the parameter of the Bernoulli distribution of y t depends on 胃 T x t . ...
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(2013) from the Bayesian stance. In Mullahy (2015), regression models for economic share data were estimated, with the shares taking zero values with nontrivial probability. Alternative regression models in the field of econometrics and applicable when zero values are present are discussed in ...
(1) Parameters are elements of the linear form xb__t. Bayesian Weibull PH regression MCMC iterations = 12,500 Random-walk Metropolis-Hastings sampling Burn-in = 2,500 MCMC sample size = 10,000 No. of subjects = 148 Number of obs = 206 No. of failures = 37 No. at risk = 1703 Acc...
Bayesian, sigmoid and semi-parametric, approaches (taking thep-value threshold as 0.01 and, similarly, a posterior probability threshold as 0.99). The NPARC approach achieves a sensitivity of 33.7, whilst the Bayesian sigmoid model a sensitivity of 36.7 and the Bayesian semi-parametric model ...
We incorporate heteroskedasticity into Bayesian Additive Regression Trees (BART) by modeling the log of the error variance parameter as a linear function of prespecified covariates. Under this scheme, the Gibbs sampling procedure for the original sum-of- trees model is easily modified, and the parame...
(2018). An adaptive bayesian lasso approach with spike-and-slab priors to identify multiple linear and nonlinear effects in structural equation models. Structural Equation Modeling: A Multidisciplinary Journal, 25, 946–960. Google Scholar Büchner, R. D., & Klein, A. G. (2020). A quasi-...
[23,24], GPs are particularly adept at modeling and analyzing complex, non-linear, and noisy data. Being a form of non-parametric Bayesian modeling, GPs find applications in regression, classification, optimization, and uncertainty quantification. In the field of cosmology, GPs have been ...
The problem of estimating nonparametric regression with associated confidence intervals is addressed. It is shown that through appropriate choice of infini... TL Mcmurry,DN Politis - 《Statistics & Probability Letters》 被引量: 78发表: 2008年 Analysis of regression confidence intervals and Bayesian cr...
Two general methods for population pharmacokinetic modeling: non-parametric adaptive grid and non-parametric Bayesian Population pharmacokinetic (PK) modeling methods can be statistically classified as either parametric or nonparametric (NP). Each classification can be div... Tatiana,Tatarinova,Michael,.....