Stochasticity among Victims of COVID-19 Pandemic

Stochasticity among Victims of COVID-19 Pandemic

Ramalingam Shanmugam,1 Gerald Ledlow,2 Karan P Singh3 1School of Health Administration, Texas State University, San Marcos, TX, 78666, USA; 2Department of Healthcare Policy, Economics and Management, School of Community and Rural Health, The University of Texas at Tyler Health Science Center, Tyler,...

Full description

Bibliographic Details
Main Authors:	Shanmugam R, Ledlow G, Singh KP
Format:	Article
Language:	English
Published:	Dove Medical Press 2022-01-01
Series:	Journal of Multidisciplinary Healthcare
Subjects:	observed heterogeneity non-observed heterogeneity over dispersion under dispersion poisson distribution binomial distribution tango’s test statistics.
Online Access:	https://www.dovepress.com/stochasticity-among-victims-of-covid-19-pandemic-peer-reviewed-fulltext-article-JMDH

Similar Items

Basic Features of the Analysis of Germination Data with Generalized Linear Mixed Models
by: Alberto Gianinetti
Published: (2020-01-01)

Modeling Under-Dispersed Count Data by the Generalized Poisson Distribution via Two New MM Algorithms
by: Xun-Jian Li, et al.
Published: (2023-03-01)

A novel approach for zero-inflated count regression model: Zero-inflated Poisson generalized-Lindley linear model with applications
by: Emrah Altun, et al.
Published: (2023-07-01)

Bivariate Poisson 2Sum-Lindley Distributions and the Associated BINAR(1) Processes
by: Muhammed Rasheed Irshad, et al.
Published: (2022-10-01)

Indexing Inefficacy of Efforts to Stop Escalation of COVID Mortality
by: Ramalingam Shanmugam, et al.
Published: (2022-12-01)

Mean and Variance Modeling of Under-Dispersed and Over-Dispersed Grouped Binary Data
by: David M. Smith, et al.
Published: (2019-07-01)

Indexing of US Counties with Overdispersed Incidences of COVID-19 Deaths
by: Ramalingam Shanmugam, et al.
Published: (2023-07-01)

The Poisson-generalised Lindley distribution and its applications
by: Weerinrada Wongrin, et al.
Published: (2016-12-01)

Multiplicative-Binomial Distribution: Some Results on Characterization, Inference and Random Data Generation
by: Elsayed A.H. Elamir
Published: (2013-05-01)

Forecasting Frequency of Delivery using Poisson Hidden Markov Models
by: S Ghorbani Gholiabad, et al.
Published: (2018-06-01)

Can Generalized Poisson model replace any other count data models? An evaluation
by: Bijesh Yadav, et al.
Published: (2021-07-01)

Does topography of rocky intertidal habitat affect aggregation of cerithiid gastropods and co-occurring macroinvertebrates?
by: Soniya Jethva, et al.
Published: (2022-04-01)

Modelling the Number of Household Visit to Health Care Centres in Some Nigeria Communities Using Count Data Regression Models
by: Samuel Olorunfemi Adams, et al.
Published: (2021-05-01)

On Underdispersed Count Kernels for Smoothing Probability Mass Functions
by: Célestin C. Kokonendji, et al.
Published: (2023-11-01)

Analysis of Text Non-Homogeneity Using Markers
by: Monika Lapėnaitė-Gedvilė, et al.
Published: (2015-12-01)

Generalized Poisson Hurdle Model for Count Data and Its Application in Ear Disease
by: Guoxin Zuo, et al.
Published: (2021-09-01)

Misspecification Tests for Log-Normal and Over-Dispersed Poisson Chain-Ladder Models
by: Jonas Harnau
Published: (2018-03-01)

A Family of Finite Mixture Distributions for Modelling Dispersion in Count Data
by: Seng Huat Ong, et al.
Published: (2023-09-01)

Application of the discrete distribution in Bayes analYsis of nature area coverage data
by: Kęstutis Dučinskas, et al.
Published: (2012-12-01)

Negative binomial regression
by: 412634 Hilbe, Joseph M.
Published: (2007)

Double Generalized Beta-Binomial and Negative Binomial Regression Models
by: EDILBERTO CEPEDA-CUERVO, et al.
Published: (2017-01-01)

The effect of landscape structure on the evolution of two alternative dispersal strategies
by: C. S. Sieger, et al.
Published: (2021-11-01)

Process Capability and Performance Indices for Discrete Data
by: Vasileios Alevizakos
Published: (2023-08-01)

The Applications of Generalized Poisson Regression Models to Insurance Claim Data
by: Pouya Faroughi, et al.
Published: (2023-12-01)

Analysis of dental caries using generalized linear and count regression models
by: Javali M. Phil, et al.
Published: (2013-11-01)

On Approximation of the Tails of the Binomial Distribution with These of the Poisson Law
by: Sergei Nagaev, et al.
Published: (2021-04-01)

Joint Modeling of Disease Pairs
by: Gergely TÓTH, et al.
Published: (2012-03-01)

A generalization of the negative binomial distribution
by: Maryam Nazemipour, et al.
Published: (2017-08-01)

Heterogeneous Overdispersed Count Data Regressions via Double-Penalized Estimations
by: Shaomin Li, et al.
Published: (2022-05-01)

Mean and Variance Modeling of Under- and Overdispersed Count Data
by: David M. Smith, et al.
Published: (2016-03-01)

Taburan binomial /
by: 263561 Aida Norliza Mohd. Ramli
Published: (2004)

Taburan binomial [compact disc] /
by: 263561 Aida Norliza Mohd. Ramli
Published: (2004)

Count regression model to predict spousal harms in Tamil Nadu
by: Elizabeth Varghese, et al.
Published: (2022-01-01)

A Conway–Maxwell–Poisson-Binomial AR(1) Model for Bounded Time Series Data
by: Huaping Chen, et al.
Published: (2023-01-01)

MODEL FOR BIONOMY OF PRIVET SAWFLY (Macrophya punctumalbum L.) (Hymenoptera, Tenthredinidae)
by: Hanna Piekarska-Boniecka, et al.
Published: (2010-09-01)

Discrimination between Some Over Dispersed Count Distributions
by: Yook-Ngor Phang, et al.
Published: (2021-03-01)

Comparing four regression techniques to explore factors governing the number of forest fires in Southeast, China
by: Qianqian Cao, et al.
Published: (2021-01-01)

Primary versus secondary source of data in observational studies and heterogeneity in meta-analyses of drug effects: a survey of major medical journals
by: Guillermo Prada-Ramallal, et al.
Published: (2018-09-01)

Geographical variation in the heterogeneity of mutualistic networks
by: Shoko Sakai, et al.
Published: (2016-01-01)

Using the computer : from binomial to normality [kasetvideo]
by: Open University. An Algorithmic Approach to Computing Course Team
Published: (1973)