Topic
Natural exponential family
About: Natural exponential family is a research topic. Over the lifetime, 1973 publications have been published within this topic receiving 60189 citations. The topic is also known as: NEF.
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4 citations
DOI•
01 Feb 1988
TL;DR: In this paper, the exponential smoothing methods of forecasting are rationalized in terms of a statistical state space model with only one primary source of randomness, and their link, in general terms, with the ARMA class of models (both stationary and nonstationary cases) is also explored.
Abstract: In this paper the exponential smoothing methods of forecasting are rationalized in terms of a statistical state space model with only one primary source of randomness. Their link, in general terms, with the ARMA class of models ( both stationary and nonstationary cases) is also explored.
4 citations
01 Jan 2008
TL;DR: On generalized order statistics from linear exponential distribution and its characterization, see as discussed by the authors for a characterization. But the characterization of the generalized order statistic is still open for further discussion and discussion.
Abstract: On generalized order statistics from linear exponential distribution and its characterization
4 citations
4 citations
Posted Content•
01 Jan 1987
TL;DR: The generalized beta of the second kind (GB2) as discussed by the authors is a principal set of distributions for modeling insurance loss processes, which can be generated as mixtures of well-known distributions, thus facilitating theoretical modeling of claims from heterogeneous populations.
Abstract: This article proposes the family of probability distributions known as the generalized beta of the second kind (GB2) as a principal set of distributions for modeling insurance loss processes. The GB2 family encompasses many commonly used distributions such as the log-normal, gamma and Weibull. It also includes distributions such as the Burr and generalized gamma which have significant potential for improving the distributional fit in many applications involving heavy-tailed distributions. Most members of the GB2 family can be generated as mixtures of well-known distributions, thus facilitating theoretical modeling of claims from heterogeneous populations. An example is presented which involves fitting the log-gamma and log-Burr distributions to a sample of fire claims. The results suggest that seemingly slight differences in modelling the tails of severity distributions can lead to substantial differences in reinsurance premiums and qualtiles of simulated total claims distributions. (A)
4 citations