Work

Parametric and nonparametric bootstrap: an analysis of indoor air data from Kuwait

Year: 2018

Type: article

Abstract: This paper discusses the performance of parametric and nonparametric bootstrap for confidence interval (CI) estimation applied to fine particulate matter (PM2.5) data. Preceding the estimation process, several models were investigated to predict PM2.5 concentrations from various tobacco smoking venues that resulted in a weighted logarithmic regression (WLS) model as a best fit. This model is then used as the base fit throughout the bootstrap estimation of the total number of burned cigarettes within an hour for a given a specific air quality level.

Source: DOAJ (DOAJ: Directory of Open Access Journals)

Authors: Sana S. Buhamra, Noriah M. Al-Kandari, Meshari Al‐Harbi

Institution: Kuwait University

Language: English

Topic: Air Quality Monitoring and Forecasting

Subfield: Environmental Engineering

Field: Environmental Science

Domain: Physical Sciences

Open Access status: gold

OpenAlex ID: W2807966022

FWCI: 0.237

Cites: 18

Cited by: 3

Related to: 10