Results 31 to 40 of about 337,913 (190)

Convergence rate to a lower tail dependence coefficient of a skew-t distribution

, 2013
We examine the rate of decay to the limit of the tail dependence coefficient of a bivariate skew t distribution which always displays asymptotic tail dependence.
Fung, Thomas, Seneta, Eugene
core   +1 more source

Bivariate Beta and Kumaraswamy Models Developed Using the Arnold-Ng Bivariate Beta Distribution

Revstat Statistical Journal, 2017
In this paper we explore some mechanisms for constructing bivariate and multivariate beta and Kumaraswamy distributions. Specifically, we focus our attention on the Arnold-Ng (2011) eight parameter bivariate beta model.
Barry Arnold , Indranil Ghosh
doaj   +1 more source

CopulaDTA: An R Package for Copula Based Bivariate Beta-Binomial Models for Diagnostic Test Accuracy Studies in a Bayesian Framework [PDF]

, 2016
The current statistical procedures implemented in statistical software packages for pooling of diagnostic test accuracy data include hSROC regression and the bivariate random-effects meta-analysis model (BRMA).
Aerts, Marc, Arbyn, Marc, Nyaga, Victoria N   +2 more
core   +3 more sources

Bayesian and Non-Bayesian Parameter Estimation for the Bivariate Odd Lindley Half-Logistic Distribution Using Progressive Type-II Censoring with Applications in Sports Data

Modelling
The Bivariate Odd Lindley Half-Logistic (BOLiHL) distribution with progressive Type-II censoring provides a powerful statistical tool for analyzing dependent data effectively.
Shruthi Polipu, Jiju Gillariose
doaj   +1 more source

Inference on P(Y [PDF]

, 2014
This paper deals with the estimation of reliability $R=P ...
Jafari, Ali Akbar, Khoolenjani, Nayereh Bagheri, Pak, Abbas   +2 more
core   +1 more source

The Bivariate Unit-Sinh-Normal Distribution and Its Related Regression Model

Mathematics, 2022
In this paper, a new bivariate absolutely continuous probability distribution is introduced. The new distribution, which is called the bivariate unit-sinh-normal (BVUSHN) distribution, arises by applying a transformation to the bivariate Birnbaum ...
Guillermo Martínez-Flórez, Artur J. Lemonte, Germán Moreno-Arenas, Roger Tovar-Falón   +3 more
doaj   +1 more source

Quantifying Bar Strength: Morphology Meets Methodology

, 2004
A set of objective bar-classification methods have been applied to the Ohio State Bright Spiral Galaxy Survey (Eskridge et al. 2002). Bivariate comparisons between methods show that all methods agree in a statistical sense.
BG Elmegreen, DL Block, G Vaucouleurs, H Wozniak, HD Curtis, JA Hackwell, PB Eskridge, PB Eskridge, R Buta, SC Odewahn   +9 more
core   +2 more sources

Farlie–Gumbel–Morgenstern Bivariate Moment Exponential Distribution and Its Inferences Based on Concomitants of Order Statistics

Stats, 2023
In this research, we design the Farlie–Gumbel–Morgenstern bivariate moment exponential distribution, a bivariate analogue of the moment exponential distribution, using the Farlie–Gumbel–Morgenstern approach.
Sasikumar Padmini Arun, Christophe Chesneau, Radhakumari Maya, Muhammed Rasheed Irshad   +3 more
doaj   +1 more source

Bivariate Beta-LSTM

, 2019
Long Short-Term Memory (LSTM) infers the long term dependency through a cell state maintained by the input and the forget gate structures, which models a gate output as a value in [0,1] through a sigmoid function.
Jang, JoonHo, Moon, Il-Chul, Shin, Seung jae, Song, Kyungwoo   +3 more
core   +1 more source

Assessment of bivariate normality

, 2004
There are three methods, which are most commonly used to assess the bivariate normality of paired data, two of which are also used to assess the multivariate normality. Nevertheless, none of the methods is very efficient or conclusive in their assessment
Sadri, Pejmon
core   +1 more source