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A Nonstationary Negative Binomial Time Series with Time-Dependent Covariates: Enterococcus Counts in Boston Harbor

Houseman, E. Andres; Coull, Brent; Shine, James - Berkeley Electronic Press - 2004

-dependent covariates; consequently we motivate the use of a Fourier basis to represent it and use penalized quasi-likelihood (PQL) for …

Persistent link: https://www.econbiz.de/10005246237

Robust Estimation of Mean and Dispersion Functions in Extended Generalized Additive Models

Croux, C.; Gijbels, I.; Prosdocimi, I. - Tilburg University, Center for Economic Research - 2010

Generalized Additive Models. However the fixed variance structure can in many cases be too restrictive. The Extended Quasi-Likelihood …

Persistent link: https://www.econbiz.de/10011090997

ESTIMATING DEMAND FOR RECREATIONAL FISHING IN ALABAMA USING TRAVEL COST MODEL

Ojumu, Oluwagbemiga; Hite, Diane; Fields, Deacue - Southern Agricultural Economics Association - SAEA - 2009

Individuals and households reveal their willingness to pay to enjoy environmental and natural resource services by engaging in outdoor recreation activities. The state of Alabama and the Black-Belt region possess significant recreational fishing resources whose qualities could be improved...

Persistent link: https://www.econbiz.de/10004973982

Loglinear Models as Item Response Models

Li, Zhushan - 2010

patterns grows exponentially as the number of items increases. To solve this computational problem, a pseudo-likelihood … developed models and the pseudolikelihood estimation method, I will present results of a series of simulation studies. To …

Persistent link: https://www.econbiz.de/10009477625

Effects of variance-function misspecification in analysis of longitudinal data

Wang, YG; Lin, X - 2005

Persistent link: https://www.econbiz.de/10009448738

Estimating the Error Distribution in the Multivariate Heteroscedastic Time Series Models

Kim, Gunky; Silvapulle, Mervyn J.; Silvapulle, Paramsothy - Department of Econometrics and Business Statistics, … - 2007

A semiparametric method is studied for estimating the dependence parameter and the joint distribution of the error term in a class of multivariate time series models when the marginal distributions of the errors are unknown. This method is a natural extension of Genest et al. (1995a) for...

Persistent link: https://www.econbiz.de/10005149050