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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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Journal ArticleDOI
TL;DR: Conditions on the probability density are derived which determine whether or not the distribution of the digits of all the unnormalized differences converges to Benford's law, shifted exponential behavior, or oscillates between the two, and it is shown that the Pareto distribution leads to oscillating behavior.
Abstract: Fix a base and let have the standard exponential distribution; the distribution of digits of base is known to be very close to Benford's law. If there exists a such that the distribution of digits of times the elements of some set is the same as that of , we say that set exhibits shifted exponential behavior base Let be i.i.d.r.v. If the 's are Unif, then as the distribution of the digits of the differences between adjacent order statistics converges to shifted exponential behavior. If instead 's come from a compactly supported distribution with uniformly bounded first and second derivatives and a second-order Taylor series expansion at each point, then the distribution of digits of any consecutive differences and all normalized differences of the order statistics exhibit shifted exponential behavior. We derive conditions on the probability density which determine whether or not the distribution of the digits of all the unnormalized differences converges to Benford's law, shifted exponential behavior, or oscillates between the two, and show that the Pareto distribution leads to oscillating behavior.

24 citations

Journal ArticleDOI
TL;DR: A new family of Marshall-Olkin extended generalized linear exponential distribution is introduced that has the advantage of being capable of modeling various shapes of aging and failure criteria and provides a better fit than some other known distributions.

23 citations

Journal ArticleDOI
TL;DR: In life testing, a two-parameter exponential distribution is often required to provide an adequate representation of the observed results as mentioned in this paper, and sufficient statistics and interval estimates for the parameters are given for the case of censored data.
Abstract: In life testing a two parameter exponential distribution is often required to provide an adequate representation of the observed results. Sufficient statistics and interval estimates for the parameters are given for the case of censored data. Numerical examples are provided.

23 citations

Journal ArticleDOI
TL;DR: In this article, the reproducing property of circular shapes or parts of conics that are important analytical shapes in geometrical modeling has been investigated and necessary and sufficient conditions for a non-stationary subdivision to have the reproduction property of exponential polynomials.
Abstract: An important capability for a subdivision scheme is the reproducing property of circular shapes or parts of conics that are important analytical shapes in geometrical modeling. In this regards, this study first provides necessary and sufficient conditions for a non-stationary subdivision to have the reproducing property of exponential polynomials. Then, the approximation order of such non-stationary schemes is discussed to quantify their approximation power. Based on these results, we see that the exponential B-spline generates exponential polynomials in the associated spaces, but it may not reproduce any exponential polynomials. Thus, we present normalized exponential B-splines that reproduce certain sets of exponential polynomials. One interesting feature is that the set of exponential polynomials to be reproduced is varied depending on the normalization factor. This provides us with the necessary accuracy and flexibility in designing target curves and surfaces. Some numerical results are presented to support the advantages of the normalized scheme by comparing them to the results without normalization.

23 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202319
202262
202114
202010
20196
201823