Search Results - subject:"Generalized Linear Models"

Rating Scales as Predictors—The Old Question of Scale Level and Some Answers

Tutz, Gerhard; Gertheiss, Jan - In: Psychometrika 79 (2014) 3, pp. 357-376

wider class of generalized linear models. Moreover, higher order differences that allow shrinkage towards a polynomial as …

Persistent link: https://www.econbiz.de/10010998760

Asymptotic expansion of the posterior density in high dimensional generalized linear models

Dasgupta, Shibasish; Khare, Kshitij; Ghosh, Malay - In: Journal of Multivariate Analysis 131 (2014) C, pp. 126-148

posteriors for generalized linear models with canonical link functions when the number of regressors grows to infinity at a …

Persistent link: https://www.econbiz.de/10010930748

Optimization Approaches to Multiplicative Tariff of Rates Estimation in Non-Life Insurance

Branda, Martin - In: Asia-Pacific Journal of Operational Research (APJOR) 31 (2014) 05, pp. 1450032-1

specific surcharge coefficients for various levels of selected risk/rating factors. We use generalized linear models (GLM) to …

Persistent link: https://www.econbiz.de/10011010827

Variable selection in high-dimensional double generalized linear models

Xu, Dengke; Zhang, Zhongzhan; Wu, Liucang - In: Statistical Papers 55 (2014) 2, pp. 327-347

In this paper we are concerned with the problems of variable selection and estimation in double generalized linear … models in which both the mean and the dispersion are allowed to depend on explanatory variables. We propose a maximum …

Persistent link: https://www.econbiz.de/10010794857

Reduced-rank vector generalized linear models with two linear predictors

Yee, Thomas W. - In: Computational Statistics & Data Analysis 71 (2014) C, pp. 889-902

Vector generalized linear models (VGLMs) as implemented in the vgamR package permit multiple parameters to depend (via …

Persistent link: https://www.econbiz.de/10010719656

Improved likelihood inference in generalized linear models

Vargas, Tiago M.; Ferrari, Silvia L.P.; Lemonte, Artur J. - In: Computational Statistics & Data Analysis 74 (2014) C, pp. 110-124

We address the issue of performing testing inference in generalized linear models when the sample size is small. This …

Persistent link: https://www.econbiz.de/10011056521

Bayesian binary regression with exponential power link

Naranjo, L.; Martín, J.; Pérez, C.J. - In: Computational Statistics & Data Analysis 71 (2014) C, pp. 464-476

A flexible Bayesian approach to a generalized linear model is proposed to describe the dependence of binary data on explanatory variables. The inverse of the exponential power cumulative distribution function is used as the link to the binary regression model. The exponential power family...

Persistent link: https://www.econbiz.de/10011056537

Family of power divergence spatial scan statistics

Zhang, Tonglin; Lin, Ge - In: Computational Statistics & Data Analysis 75 (2014) C, pp. 162-178

The classical spatial scan test, which derived by maximizing the likelihood ratio statistic over a collection of cluster candidates, is widely used in spatial cluster detection. As the likelihood ratio statistic is only a special case in the family of power divergence (PD) goodness-of-fit...

Persistent link: https://www.econbiz.de/10010871327

Power and sample size calculations for Poisson and zero-inflated Poisson regression models

Channouf, Nabil; Fredette, Marc; MacGibbon, Brenda - In: Computational Statistics & Data Analysis 72 (2014) C, pp. 241-251

Although sample size calculations for testing a parameter in the Poisson regression model have been previously done, very little attention has been given to the effect of the correlation structure of the explanatory covariates on the sample size. A method to calculate the sample size for the...

Persistent link: https://www.econbiz.de/10010871488

Bayesian estimation of volatility with moment-based nonlinear stochastic filters

Grothe, Oliver - 2006

Persistent link: https://www.econbiz.de/10013409325