Search Results - subject:"Variance function"

A note on the construction of locally D- and DS-optimal designs for the binary logistic model with several explanatory variables

Kabera, M. Gaëtan; Haines, Linda M.; Ndlovu, Principal - In: Statistics & Probability Letters 82 (2012) 5, pp. 865-870

An explicit formulation of D- and DS-optimal designs for the binary logistic regression model in several variables, without interaction between the variables, is presented. The proof of the optimality of the designs is “traditional” in the sense that it invokes the Equivalence Theorem, and...

Persistent link: https://www.econbiz.de/10011039796

Spline nonparametric quasi-likelihood regression within the frame of the accelerated failure time model

Yu, Lili; Peace, Karl E. - In: Computational Statistics & Data Analysis 56 (2012) 9, pp. 2675-2687

proposed for this model. The method uses nonparametric quasi-likelihood in which the variance function is estimated by … nonparametric variance function estimator is derived. It is shown that the regression coefficient estimators are asymptotically …

Persistent link: https://www.econbiz.de/10010577704

On the robustness of two-stage estimators

Zhelonkin, Mikhail; Genton, Marc G.; Ronchetti, Elvezio - In: Statistics & Probability Letters 82 (2012) 4, pp. 726-732

of two-stage models. We derive the influence function, the change-of-variance function, and the asymptotic variance of a …

Persistent link: https://www.econbiz.de/10010571794

On the estimation of a monotone conditional variance in nonparametric regression

Dette, Holger; Pilz, Kay F. - 2004

A monotone estimate of the conditional variance function in a heteroscedastic, nonpara- metric regression model is … function and yields an esti- mate of the inverse variance function. The final monotone estimate of the variance function is … proposed. The method is based on the application of a kernel density estimate to an unconstrained estimate of the variance …

Persistent link: https://www.econbiz.de/10010296626

On the estimation of a monotone conditional variance in nonparametric regression

Dette, Holger; Pilz, Kay F. - Institut für Wirtschafts- und Sozialstatistik, … - 2004

Persistent link: https://www.econbiz.de/10009216878

How to compare interpretatively different models for the conditional variance function

Juutilainen, Ilmari; Roning, Juha - In: Journal of Applied Statistics 37 (2010) 6, pp. 983-997

to depend on the explanatory variables via a parametric or non-parametric variance function. The variance function has …

Persistent link: https://www.econbiz.de/10008674934

A note on the prior parameter choice in finite mixture models of distributions from exponential families

Rufo, M.; Martín, J.; Pérez, C. - In: Computational Statistics 25 (2010) 3, pp. 537-550

Persistent link: https://www.econbiz.de/10008456129

On the estimation of a monotone conditional variance in nonparametric regression

Dette, Holger; Pilz, Kay - In: Annals of the Institute of Statistical Mathematics 61 (2009) 1, pp. 111-141

Persistent link: https://www.econbiz.de/10005395591

Weibull extension of bivariate exponential regression model with different frailty distributions

Hanagal, David - In: Statistical Papers 50 (2009) 1, pp. 29-49

Persistent link: https://www.econbiz.de/10005615801

Managerial Risk Attitudes and Firm Performance in Ghanaian Manufacturing: an Empirical Analysis Based on Experimental Data

Söderbom, Måns; Pattillo, Catherine - Department of Economics, Oxford University - 2000

Ghanaian manufacturing firms face a highly risky environment. Firms may attempt to manage these risks by undertaking production, input, and investment strategies designed to lower profit variability. Mean-variance analysis implies, however, that these strategies involve a trade-off with lower...

Persistent link: https://www.econbiz.de/10011152491