Improved Semiparametric Time Series Models of Air Pollution and Mortality

DOI10.1198/016214504000000656zbMath1055.62132OpenAlexW1977456601MaRDI QIDQ4651025

Aidan McDermott, Francesca Dominici, Trevor Hastie

Publication date: 21 February 2005

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1198/016214504000000656

zbMATH Keywords

mean squared errorsemiparametric regressionbandwidth selectiongeneralized additive modelparticulate matter

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to environmental and related topics (62P12) Generalized linear models (logistic models) (62J12)

Related Items (13)

Time series modeling of pathogen‐specific disease probabilities with subsampled data ⋮ Bias correction in estimation of public health risk attributable to short‐term air pollution exposure ⋮ Measurement error in air pollution epidemiology: guidance for uncertain times ⋮ The importance of scale for spatial-confounding bias and precision of spatial regression estimators ⋮ Semiparametric regression during 2003--2007 ⋮ Bayesian modeling of autoregressive partial linear models with scale mixture of normal errors ⋮ Rejoinder ⋮ The role of weather in meningitis outbreaks in Navrongo, Ghana: a generalized additive modeling approach ⋮ Bayesian Effect Estimation Accounting for Adjustment Uncertainty ⋮ GENERALIZED EXTREME VALUE ADDITIVE MODEL ANALYSIS VIA MEAN FIELD VARIATIONAL BAYES ⋮ Bayesian Distributed Lag Models: Estimating Effects of Particulate Matter Air Pollution on Daily Mortality ⋮ Parametric and semi-parametric approaches in the analysis of short-term effects of air pollution on health ⋮ Estimating acute air pollution health effects from cohort study data

Uses Software

• S-PLUS

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