Results 11 to 20 of about 29,960 (243)

A Mixture Autoregressive Model Based on an Asymmetric Exponential Power Distribution

Axioms, 2023
In nonlinear time series analysis, the mixture autoregressive model (MAR) is an effective statistical tool to capture the multimodality of data. However, the traditional methods usually need to assume that the error follows a specific distribution that ...
Yunlu Jiang, Zehong Zhuang
doaj   +1 more source

Hyperspectral Denoising Using Asymmetric Noise Modeling Deep Image Prior

Remote Sensing, 2023
Deep image prior (DIP) is a powerful technique for image restoration that leverages an untrained network as a handcrafted prior. DIP can also be used for hyperspectral image (HSI) denoising tasks and has achieved impressive performance.
Yifan Wang, Shuang Xu, Xiangyong Cao, Qiao Ke, Teng-Yu Ji, Xiangxiang Zhu   +5 more
doaj   +1 more source

Some Generalizations of Weibull Distribution and Related Processes [PDF]

Journal of Statistical Theory and Applications (JSTA), 2015
A new class of distributions containing Marshall-Olkin extended Weibull distribution is introduced. The role of this distribution in the study of minification process is established.
K. Jayakumar, M. Girish Babu
doaj   +1 more source

RECORD RANGES FOR SAMPLES FROM ASYMMETRICAL LAPLACE DISTRIBUTIONS [PDF]

Journal of Statistical Theory and Applications, 2018
The representations of record ranges via sums of independent identically distributed exponential random variables are obtained for asymmetrical Laplace distributions. This result generalizes the corresponding relations for record values in the cases of exponential and negative exponential ...
I.V. BELKOV, M. AHSANULLAH, V. B. NEVZOROV   +2 more
openaire   +2 more sources

Asymmetric clusters and outliers: Mixtures of multivariate contaminated shifted asymmetric Laplace distributions [PDF]

Computational Statistics & Data Analysis, 2019
Mixtures of multivariate contaminated shifted asymmetric Laplace distributions are developed for handling asymmetric clusters in the presence of outliers (also referred to as bad points herein). In addition to the parameters of the related non-contaminated mixture, for each (asymmetric) cluster, our model has one parameter controlling the proportion of
Morris K., Punzo A., McNicholas P. D., Browne R. P.   +3 more
openaire   +3 more sources

Poissonian resetting of subdiffusion in a linear potential

Condensed Matter Physics, 2023
Resetting a stochastic process is an important problem describing the evolution of physical, biological and other systems which are continually returned to their certain fixed point. We consider the motion of a subdiffusive particle with a constant drift
A. A. Stanislavsky
doaj   +1 more source

Bayesian composite quantile regression for the single-index model.

PLoS ONE, 2023
By using a Gaussian process prior and a location-scale mixture representation of the asymmetric Laplace distribution, we develop a Bayesian analysis for the composite quantile single-index regression model.
Xiaohui Yuan, Xuefei Xiang, Xinran Zhang
doaj   +1 more source

Quantile regression for longitudinal data using the asymmetric Laplace distribution [PDF]

Biostatistics, 2006
In longitudinal studies, measurements of the same individuals are taken repeatedly through time. Often, the primary goal is to characterize the change in response over time and the factors that influence change. Factors can affect not only the location but also more generally the shape of the distribution of the response over time.
GERACI M, BOTTAI M
openaire   +2 more sources

Simulation Study The Using of Bayesian Quantile Regression in Nonnormal Error

Cauchy: Jurnal Matematika Murni dan Aplikasi, 2018
The purposes of this paper is  to introduce the ability of the Bayesian quantile regression method in overcoming the problem of the nonnormal errors using asymmetric laplace distribution on simulation study.
Catrin Muharisa, Ferra Yanuar, Dodi Devianto   +2 more
doaj   +1 more source

evgam: An R Package for Generalized Additive Extreme Value Models

Journal of Statistical Software, 2022
This article introduces the R package evgam. The package provides functions for fitting extreme value distributions. These include the generalized extreme value and generalized Pareto distributions.
Benjamin D. Youngman
doaj   +1 more source