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Journal ArticleDOI

Hierarchical credibility: analysis of a random effect linear model with nested classification

Ragnar Norberg
- 01 Jul 1986 - 
- Vol. 1986, pp 204-222
TLDR
In this article, a random coefficient regression model with multi-stage nested classification is considered, and linear Bayes estimators are obtained for random effects at all stages, and estimators of the structural parameters are proposed.
Abstract
A random coefficient regression model with multi-stage nested classification is considered. Linear Bayes estimators are obtained for random effects at all stages, and estimators of the structural parameters are proposed.

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Citations
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MonographDOI

Longitudinal and Panel Data: Analysis and Applications in the Social Sciences

TL;DR: In this paper, the authors introduce the foundations of longitudinal and panel data analysis at a level suitable for quantitatively oriented graduate social science students as well as individual researchers, emphasizing mathematical and statistical fundamentals but also describing substantive applications from across the social sciences, showing the breadth and scope that these models enjoy.
Journal ArticleDOI

The growth curve model: a review

TL;DR: In this paper, a survey is given of papers which have influenced or have been influenced by the growth curve model due to Potthoff & Roy (1964), and a review covers, among others, methods of estimating parameters, the canonical version of the model, tests, extensions, incomplete data, Bayesian approaches and covariance structures.
Journal ArticleDOI

A longitudinal data analysis interpretation of credibility models

TL;DR: The primary contribution to actuarial science is to demonstrate that many additive credibility models can be expressed as special cases of the longitudinal data model, which unify the many existing credibility models with this framework.
Journal ArticleDOI

A comparative analysis of 30 bonus-malus systems

Jean Lemaire, +1 more
- 01 Nov 1994 - 
TL;DR: In this paper, the authors compared 22 automobile third party insurance merit-rating systems of 22 countries, using as main tools the stationary average premium level, the variability of the policyholders' payments, their elasticity with respect to the claim frequency, and the magnitude of the hunger for bonus.

A bibliography on variance components an introduction and an update: 1984-2002

TL;DR: In particular, the study of variance through a class of linear models known as random and mixed models is a central topic in statistics with wide ramifications in both theory and applications as discussed by the authors.
References
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Book

An Introduction to Multivariate Statistical Analysis

TL;DR: In this article, the distribution of the Mean Vector and the Covariance Matrix and the Generalized T2-Statistic is analyzed. But the distribution is not shown to be independent of sets of Variates.
Journal ArticleDOI

The Analysis of Variance

TL;DR: In this paper, the basic theory of analysis of variance by considering several different mathematical models is examined, including fixed-effects models with independent observations of equal variance and other models with different observations of variance.
Book

Optimal Statistical Decisions

TL;DR: In this article, the authors present a survey of probability theory in the context of sample spaces and decision problems, including the following: 1.1 Experiments and Sample Spaces, and Probability 2.2.3 Random Variables, Random Vectors and Distributions Functions.
Book

Bayesian inference in statistical analysis

TL;DR: In this article, the effect of non-normality on inference about a population mean with generalizations was investigated. But the authors focused on the effect on the mean with information from more than one source.