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Natural Gradient Flow in the Mixture Geometry of a Discrete Exponential Family [PDF]

open access: yesEntropy, 2015
In this paper, we study Amari’s natural gradient flows of real functions defined on the densities belonging to an exponential family on a finite sample space.
Luigi Malagò, Giovanni Pistone
doaj   +5 more sources

Small area estimation with spatially varying natural exponential families [PDF]

open access: yesJournal of Statistical Computation and Simulation, 2020
Two-stage hierarchical models have been widely used in small area estimation to produce indirect estimates of areal means. When the areas are treated exchangeably and the model parameters are assumed to be the same over all areas, we might lose the efficiency in the presence of spatial heterogeneity.
Shonosuke Sugasawa   +2 more
openaire   +4 more sources

On Computationally Efficient Learning of Exponential Family Distributions [PDF]

open access: yesarXiv.org, 2023
We consider the classical problem of learning, with arbitrary accuracy, the natural parameters of a $k$-parameter truncated \textit{minimal} exponential family from i.i.d. samples in a computationally and statistically efficient manner.
Abhin Shah, Devavrat Shah, G. Wornell
semanticscholar   +1 more source

The Exponential Dispersion Model Generated by the Landau Distribution—A Comprehensive Review and Further Developments

open access: yesMathematics, 2023
The paper comprehensively studies the natural exponential family and its associated exponential dispersion model generated by the Landau distribution. These families exhibit probabilistic and statistical properties and are suitable for modeling skewed ...
Shaul K. Bar-Lev
doaj   +1 more source

Cumulant-Based Goodness-of-Fit Tests for the Tweedie, Bar-Lev and Enis Class of Distributions

open access: yesMathematics, 2023
The class of natural exponential families (NEFs) of distributions having power variance functions (NEF-PVFs) is huge (uncountable), with enormous applications in various fields.
Shaul K. Bar-Lev   +4 more
doaj   +1 more source

A New Class of Counting Distributions Embedded in the Lee–Carter Model for Mortality Projections: A Bayesian Approach

open access: yesRisks, 2022
The Lee–Carter model, the dominant mortality projection modeling in the literature, was criticized for its homoscedastic error assumption. This was corrected in extensions to the model based on the assumption that the number of deaths follows Poisson or ...
Yaser Awad, Shaul K. Bar-Lev, Udi Makov
doaj   +1 more source

The Large Arcsine Exponential Dispersion Model—Properties and Applications to Count Data and Insurance Risk

open access: yesMathematics, 2022
The large arcsine exponential dispersion model (LAEDM) is a class of three-parameter distributions on the non-negative integers. These distributions show the specific characteristics of being leptokurtic, zero-inflated, overdispersed, and skewed to the ...
Shaul K. Bar-Lev, Ad Ridder
doaj   +1 more source

Exponential Families with External Parameters

open access: yesEntropy, 2022
In this paper we introduce a class of statistical models consisting of exponential families depending on additional parameters, called external parameters.
Marco Favretti
doaj   +1 more source

Location and scale behaviour of the quantiles of a natural exponential family [PDF]

open access: yesE S A I M: Probability & Statistics, 2018
Let P0 be a probability on the real line generating a natural exponential family (Pt)t∈ℝ. Fix α in (0, 1). We show that the property that Pt((−∞, t)) ≤ α ≤ Pt((−∞, t]) for all t implies that there exists a number μα such that P0 is the Gaussian ...
M. Piccioni   +2 more
semanticscholar   +1 more source

Rényi Cross-Entropy Measures for Common Distributions and Processes with Memory

open access: yesEntropy, 2022
Two Rényi-type generalizations of the Shannon cross-entropy, the Rényi cross-entropy and the Natural Rényi cross-entropy, were recently used as loss functions for the improved design of deep learning generative adversarial networks.
Ferenc Cole Thierrin   +2 more
doaj   +1 more source

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