Results 11 to 20 of about 46,519 (215)

Predicting cyanobacteria abundance with Bayesian zero-inflated models

Journal of Hydroinformatics, 2023
Cyanobacterial blooms are a persistent concern to water management and treatment, with blooms potentially causing the release of toxins and degrading water quality.
Yirao Zhang, Nicolas M. Peleato
doaj   +1 more source

MODELLING ZERO-INFLATED OVER DISPERSED DENGUE DATA VIA ZERO-INFLATED POISSON INVERSE GAUSSIAN REGRESSION MODEL: A CASE STUDY OF BANGLADESH [PDF]

Acta Scientifica Malaysia
Bangladesh has been noted for experiencing some of the most susceptible dengue outbreaks in Asia; the country’s location, dense population, and changing environment all play major roles in this.
Sukanta Chakraborty, Soma Chowdhury Biswas   +1 more
doaj   +1 more source

Randomized quantile residuals for diagnosing zero-inflated generalized linear mixed models with applications to microbiome count data

BMC Bioinformatics, 2021
Background For differential abundance analysis, zero-inflated generalized linear models, typically zero-inflated NB models, have been increasingly used to model microbiome and other sequencing count data.
Wei Bai, Mei Dong, Longhai Li, Cindy Feng, Wei Xu   +4 more
doaj   +1 more source

Assessment and Selection of Competing Models for Zero-Inflated Microbiome Data. [PDF]

PLoS ONE, 2015
Typical data in a microbiome study consist of the operational taxonomic unit (OTU) counts that have the characteristic of excess zeros, which are often ignored by investigators.
Lizhen Xu, Andrew D Paterson, Williams Turpin, Wei Xu   +3 more
doaj   +1 more source

A New Zero-Inflated Negative Binomial Multilevel Model for Forecasting the Demand of Disaster Relief Supplies in the State of Sao Paulo, Brazil

Mathematics, 2022
This article presents the results of the implementation of a forecasting model, to predict the relief materials needed for assisting in decisions prior to natural disasters, thus filling a gap in the exploration of Generalized Linear Mixed Models (GLMM ...
Camila Pareja Yale, Hugo Tsugunobu Yoshida Yoshizaki, Luiz Paulo Fávero   +2 more
doaj   +1 more source

Zero-Inflated Data Clustering Using Graph Neural Networks with Zero-Inflated Likelihood

Stats
Sparse count data, such as patent document–keyword matrices, often contain excessive zeros and overdispersion, making conventional distance-based clustering methods less suitable.
Sunghae Jun
doaj   +1 more source

Zero inflated negative binomial-generalized exponential distributionand its applications [PDF]

Songklanakarin Journal of Science and Technology (SJST), 2014
In this paper, we propose a new zero inflated distribution, namely, the zero inflated negative binomial-generalized exponential (ZINB-GE) distribution. The new distribution is used for count data with extra zeros and is an alternative for data analysis
Sirinapa Aryuyuen, Winai Bodhisuwan, Thidaporn Supapakorn   +2 more
doaj  

A New Zero–Inflated Regression Model with Applications to Australian Health Survey and Biochemistry Graduate Students Data

Journal of Mathematics
In this study, we propose a new zero-inflated regression model as an alternative to zero-inflated regression models, such as the zero-inflated Poisson, zero-inflated negative binomial, zero-inflated hurdle-Poisson, and zero-inflated hurdle negative ...
Caner Tanış, Mahmoud M. Mansour, Enayat M. Abd Elrazik, Christophe Chesneau, Hazem Al-Mofleh, Ahmed Z. Afify   +5 more
doaj   +1 more source

The impact of leukocyte‐associated RNA retention on platelet RNA‐based cancer detection

Molecular Oncology, EarlyView.
Platelets carry RNA signals that may help detect cancer, but platelet samples can also retain RNA from white blood cells. We found that this retained white blood cell signal did not significantly affect machine learning cancer classification, suggesting that the cancer‐related RNA signal in platelets is largely independent of leukocyte‐associated RNA ...
Michał Sieczczyński, Krzysztof Pastuszak, Anna Samelak‐Czajka, Zuzanna Cemka, Paulina Jackowiak, Tomasz Stefaniak, Sylwia Łapińska‐Szumczyk, Jacek Jassem, Anna J. Żaczek, Matthew T. Rondina, Myron G. Best, Sjors G. J. G. In 't Veld, Anna Supernat   +12 more
wiley   +1 more source

Acute Kidney Injury After Mechanical Thrombectomy for Stroke in Patients With Pre‐Existing Renal Impairment

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives Acute kidney injury (AKI) is a common but often underrecognized complication in ischemic stroke patients undergoing mechanical thrombectomy, particularly among those with pre‐existing renal impairment. This study evaluated the incidence, risk factors, and clinical impact of AKI in this high‐risk population.
Michał Borończyk, Marcel Pilarek, Emilia Jaworska, Natalia Kardas, Oliwia Barnaś, Julia Woźniak, Iga Machała, Julia Węgrzynek‐Gallina, Joanna Siuda, Anna Hawrot‐Kawecka, Anetta Lasek‐Bal   +10 more
wiley   +1 more source