2007 Bayesian multivariate linear regression with application to change point models in hydrometeorological variables. Water Resour. Res. 43, W08401. (doi:10.1029/2005WR004835)Seidou O, Asselin JJ, Ouarda T (2007) Bayesian multivariate linear regression with application to change point models in ...
For details on the analytically tractable posterior distributions offered by the Bayesian linear regression model framework in Econometrics Toolbox, see Analytically Tractable Posteriors. Otherwise, you must use numerical integration techniques to compute integrals of h(β,σ2) with respect to posterior ...
Stone CJ (1985) Additive regression and other nonparametric models. Ann Stat 13(2):689–705 Article MathSciNet MATH Google Scholar Teuquia ON, Ren J, Planchet F (2014) Internal model in life insurance: application of least squares Monte-Carlo in risk assessment van der vaart AW, Wellner...
The overall summary is: You can first try linear regression. If this is not appropriate for your problem you can then try pre-transforming your y-data (a log-like or logit transform) and seeing if that fits better. However, if you transform your y-data you are using a new error model...
Section 6 uses the empirical relationship between stock returns and dividend yields to illustrate the application of this diagnostic. Section 7 contains some concluding comments. Some of the technical derivations are relegated to appendices. The computer code for the simulation exercise is available as ...
Examples based on a large data set arising from an energy-conservation study are given to demonstrate the application of the methods. 展开 关键词: Cross-validation Linear models Subset selection DOI: 10.1080/01621459.1988.10478694 被引量: 674 ...
Bayesian linear regression solves the problem of overfitting in maximum likelihood estimation. Moreover, it makes full use of data samples and is suitable for modeling complex data [18,19]. In addition to regression, Bayesian reasoning can also be applied in other fields. Some researchers have ...
A Bayesian analysis of regression models with continuous errors with application to longitudinal studies by L. D. Broemeling and P. Cook, Statistics in ... JA Nelder - 《Statistics in Medicine》 被引量: 0发表: 1998年 Parameter changes in a regression model with autocorrelated errors This study...
Bayesian linear regression solves the problem of overfitting in maximum likelihood estimation. Moreover, it makes full use of data samples and is suitable for modeling complex data [18,19]. In addition to regression, Bayesian reasoning can also be applied in other fields. Some researchers have ...
Mixed model based approaches for semiparametric regression have gained much interest in recent years, both in theory and application. They provide a unifie... T Kneib,L Fahrmeir - 《Scandinavian Journal of Statistics》 被引量: 148发表: 2010年 Structured additive regression for overdispersed and ze...