Results 21 to 30 of about 79,690 (134)

PEMODELAN DATA KEMATIAN BAYI DENGAN GEOGRAPHICALLY WEIGHTED NEGATIVE BINOMIAL REGRESSION

open access: yesMedia Statistika, 2016
Overdispersion phenomenon and the influence of location or spatial aspect on data are handled using Binomial Geographically Weighted Regression (GWNBR).
Riza F. Ramadhan, Robert Kurniawan
doaj   +1 more source

Disease mapping via negative binomial regression M-quantiles [PDF]

open access: yesStatistics in Medicine, 2014
23 pages, 7 ...
R. Chambers   +2 more
openaire   +4 more sources

ZERO-INFLATED NEGATIVE BINOMIAL REGRESSION FOR DIFFERENTIAL ABUNDANCE TESTING IN MICROBIOME STUDIES

open access: yesJournal of Bioinformatics and Genomics, 2016
Motivation: The human microbiome plays an important role in human health and disease. The composition of the human microbiome is influenced by multiple factors and understanding these factors is critical to elucidate the role of the microbiome in health ...
Xinyan Zhang, Himel Mallick, Nengjun Yi
doaj   +1 more source

Count data regression modeling: an application to spontaneous abortion

open access: yesReproductive Health, 2020
Background In India, around 20,000 women die every year due to abortion-related complications. In count data modeling, there is sometimes a prevalence of zero counts.
Prashant Verma   +3 more
doaj   +1 more source

Negative binomial factor regression with application to microbiome data analysis [PDF]

open access: yesStatistics in Medicine, 2021
Abstract The human microbiome provides essential physiological functions and helps maintain host homeostasis via the formation of intricate ecological host‐microbiome relationships. While it is well established that the lifestyle of the host, dietary preferences, demographic background, and health status can influence microbial ...
Aditya K. Mishra, Christian L. Müller
openaire   +3 more sources

Re-sampling Techniques in Count Data Regression Models [PDF]

open access: yesالمجلة العراقية للعلوم الاحصائية, 2012
Modeling count variables is a common task in many application areas such as economics, social sciences, and medicine. The classical Poisson regression model for count data is often used and it is limited in these disciplines since count data sets ...
Zakariya Y. Algamal
doaj   +1 more source

Fertility among Northern Nigeria women and associated factors: Negative binomial regression model approach

open access: yesBabcock University Medical Journal, 2023
Objective:  The 2020 sustainable development progress report shows that human population growth is a critical barrier to achieving the Sustainable Development Goals (SDG).
Kolawole Oritogun   +2 more
doaj   +1 more source

Negative Binomial Kumaraswamy-G Cure Rate Regression Model [PDF]

open access: yesJournal of Risk and Financial Management, 2018
In survival analysis, the presence of elements not susceptible to the event of interest is very common. These elements lead to what is called a fraction cure, cure rate, or even long-term survivors. In this paper, we propose a unified approach using the negative binomial distribution for modeling cure rates under the Kumaraswamy family of distributions.
Amanda D’Andrea   +3 more
openaire   +2 more sources

PENANGANAN OVERDISPERSI PADA MODEL REGRESI POISSON MENGGUNAKAN MODEL REGRESI BINOMIAL NEGATIF

open access: yesMedia Statistika, 2011
Poisson regression is the most popular tool for modeling the relationship between a discrete data in the response variable and a set of predictors with continue, discrete, categoric or mix data.
Rio Tongaril Simarmata, Dwi Ispriyanti
doaj   +1 more source

Factors Affecting The Use Of WTO Fiscal Protection Instruments

open access: yesInternational Journal of Public Finance, 2021
Many countries, especially developed countries, have been trying to liberalize international trade for many years. Although it is intended to liberalize international trade, countries do not hesitate to use protection policy instruments. Within the means
Göksel Karaş
doaj   +1 more source

Home - About - Disclaimer - Privacy