A new neutrosophic sign test: An application to COVID-19 data

Autor: Wajiha Batool Awan, Muhammad Saleem, Muhammad Aslam, Huma Shakeel, Rehan Ahmad Khan Sherwani, Muhammad Farooq
Jazyk: angličtina
Rok vydání: 2021
Předmět:
RNA viruses
Viral Diseases
Coronaviruses
Computer science
Test Statistics
Social Sciences
computer.software_genre
Mathematical and Statistical Techniques
Medical Conditions
Cognition
Medicine and Health Sciences
Psychology
Sign test
Pakistan
Pathology and laboratory medicine
Virus Testing
Statistical Data
Parametric statistics
Multidisciplinary
Statistics
Medical microbiology
Test (assessment)
Monte Carlo method
Infectious Diseases
Physical Sciences
Viruses
Medicine
Data mining
SARS CoV 2
Pathogens
Indeterminate
Algorithms
Research Article
Computer and Information Sciences
SARS coronavirus
Science
Decision Making
Research and Analysis Methods
Models
Biological
Microbiology
Fuzzy logic
Fuzzy Logic
Diagnostic Medicine
Humans
Statistical Methods
Statistical hypothesis testing
Biology and life sciences
SARS-CoV-2
Organisms
Viral pathogens
Cognitive Psychology
Nonparametric statistics
COVID-19
Covid 19
Computing Methods
Microbial pathogens
Sample size determination
Cognitive Science
computer
Mathematics
Neuroscience
Zdroj: PLoS ONE, Vol 16, Iss 8, p e0255671 (2021)
PLoS ONE
ISSN: 1932-6203
Popis: The Sign test is a famous nonparametric test from classical statistics used to assess the one or two sample averages. The test is practical when the sample size is small, or the distributional assumption under a parametric test does not satisfy. One of the limitations of the Sign test is the exact form of the data, and the existing methodology of the test does not cover the interval-valued data. The interval-valued data often comes from the fuzzy logic where the experiment’s information is not sure and possesses some kind of vagueness, uncertainty or indeterminacy. This research proposed a modified version of the Sign test by considering the indeterminate state and the exact form of the data—the newly proposed sign test methodology is designed for both one-sample and two-sample hypothesis testing problems. The performance of the proposed modified versions of the Sign test is evaluated through two real-life data examples comprised of covid-19 reproduction rate and covid-positive daily occupancy in ICU in Pakistan. The findings of the study suggested that our proposed methodologies are suitable in nonparametric decision-making problems with an interval–valued data. Therefore, applying the new neutrosophic sign test is explicitly recommended in biomedical sciences, engineering, and other statistical fields under an indeterminate environment.
Databáze: OpenAIRE
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