Application of Principal Component Analysis to Time Series of Daily Air Pollution and Mortality PDF Download

Author: C. M. Quant
Publisher:
ISBN:
Category :
Languages : en
Pages : 89

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Author: William W. S. Wei
Publisher: John Wiley & Sons
ISBN: 1119502853
Category : Mathematics
Languages : en
Pages : 536

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An essential guide on high dimensional multivariate time series including all the latest topics from one of the leading experts in the field Following the highly successful and much lauded book, Time Series Analysis—Univariate and Multivariate Methods, this new work by William W.S. Wei focuses on high dimensional multivariate time series, and is illustrated with numerous high dimensional empirical time series. Beginning with the fundamentalconcepts and issues of multivariate time series analysis,this book covers many topics that are not found in general multivariate time series books. Some of these are repeated measurements, space-time series modelling, and dimension reduction. The book also looks at vector time series models, multivariate time series regression models, and principle component analysis of multivariate time series. Additionally, it provides readers with information on factor analysis of multivariate time series, multivariate GARCH models, and multivariate spectral analysis of time series. With the development of computers and the internet, we have increased potential for data exploration. In the next few years, dimension will become a more serious problem. Multivariate Time Series Analysis and its Applications provides some initial solutions, which may encourage the development of related software needed for the high dimensional multivariate time series analysis. Written by bestselling author and leading expert in the field Covers topics not yet explored in current multivariate books Features classroom tested material Written specifically for time series courses Multivariate Time Series Analysis and its Applications is designed for an advanced time series analysis course. It is a must-have for anyone studying time series analysis and is also relevant for students in economics, biostatistics, and engineering.

Author: Ying Jiang
Publisher:
ISBN:
Category : Air
Languages : en
Pages : 216

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A number of time series studies provide evidence that air pollution levels are associated with daily death counts. Most of these studies explain these associations by using Poisson log-linear regression models, after allowing for possible confounders. However, the findings of these time series studies suffer from several problems, of which the most significant is conflicting results from different approaches to model selection. To address this problem, this dissertation compares the statistical properties of these approaches, including those with and without model selection uncertainty. In the simulation experiments, the sensitivity of these statistical properties to the choice of bootstrap resampling schemes, including a parametric bootstrap and residual-based bootstrap, is investigated. Simulation results indicate that regardless of the type of resampling schemes used, Bayesian model averaging methods based on Akaike's Information Criterion (BMA-aic) perform well in predicting the mortality effect of particulate matter. Additionally, rather than the standard use of the Bayesian Information Criterion (BIC), this study suggests using Akaike's Information Criterion (AIC) for the data from Chicago, if prediction is the goal. Thus, when predicting seasonal mortality effects of air pollution in Chicago, this dissertation incorporates AIC to identify the pattern of unmeasured confounding effects for each season in that city. A common approach to control for unmeasured confounding effects is to adopt a natural cubic spline function of time with fixed degrees of freedom per year. This approach uses an annual adjustment for these effects. However, in reality, these effects may vary according to season; given this, seasonal adjustments for these effects are advocated. As such, this raises the issue of how to control the confounders adequately in the natural cubic spline function. To resolve this issue, a model is proposed to explain the association between particulate matter and mortality after allowing for the seasonal patterns of confounders. AIC is used to select the degrees of freedom for each season. The results indicate a high mortality level during seasons with high particulate matter concentrations.

Author: Roger D. Peng
Publisher: Springer Science & Business Media
ISBN: 0387781676
Category : Medical
Languages : en
Pages : 151

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As an area of statistical application, environmental epidemiology and more speci cally, the estimation of health risk associated with the exposure to - vironmental agents, has led to the development of several statistical methods and software that can then be applied to other scienti c areas. The stat- tical analyses aimed at addressing questions in environmental epidemiology have the following characteristics. Often the signal-to-noise ratio in the data is low and the targets of inference are inherently small risks. These constraints typically lead to the development and use of more sophisticated (and pot- tially less transparent) statistical models and the integration of large hi- dimensional databases. New technologies and the widespread availability of powerful computing are also adding to the complexities of scienti c inves- gation by allowing researchers to t large numbers of models and search over many sets of variables. As the number of variables measured increases, so do the degrees of freedom for in uencing the association between a risk factor and an outcome of interest. We have written this book, in part, to describe our experiences developing and applying statistical methods for the estimation for air pollution health e ects. Our experience has convinced us that the application of modern s- tistical methodology in a reproducible manner can bring to bear subst- tial bene ts to policy-makers and scientists in this area. We believe that the methods described in this book are applicable to other areas of environmental epidemiology, particularly those areas involving spatial{temporal exposures.

Author: Ralf Koppmann
Publisher: John Wiley & Sons
ISBN: 0470994150
Category : Science
Languages : en
Pages : 512

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Every day, large quantities of volatile organic compounds (VOCs) are emitted into the atmosphere from both anthropogenic and natural sources. The formation of gaseous and particulate secondary products caused by oxidation of VOCs is one of the largest unknowns in the quantitative prediction of the earth’s climate on a regional and global scale, and on the understanding of local air quality. To be able to model and control their impact, it is essential to understand the sources of VOCs, their distribution in the atmosphere and the chemical transformations which remove these compounds from the atmosphere. In recent years techniques for the analysis of organic compounds in the atmosphere have been developed to increase the spectrum of detectable compounds and their detection limits. New methods have been introduced to increase the time resolution of those measurements and to resolve more complex mixtures of organic compounds. Volatile Organic Compounds in the Atmosphere describes the current state of knowledge of the chemistry of VOCs as well as the methods and techniques to analyse gaseous and particulate organic compounds in the atmosphere. The aim is to provide an authoritative review to address the needs of both graduate students and active researchers in the field of atmospheric chemistry research.

Author:
Publisher:
ISBN:
Category : Environmental health
Languages : en
Pages : 1490

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Author: Francesca Dominici
Publisher:
ISBN:
Category :
Languages : en
Pages : 33

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Author: Roberta Charon Gwynn
Publisher:
ISBN: 9780599159433
Category :
Languages : en
Pages : 277

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Author: Andrzej Chmielewski
Publisher: BoD – Books on Demand
ISBN: 9533075260
Category : Technology & Engineering
Languages : en
Pages : 268

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Book Description
The book addresses the subjects related to the selected aspects of pollutants emission, monitoring and their effects. The most of recent publications concentrated on the review of the pollutants emissions from industry, especially power sector. In this one emissions from opencast mining and transport are addressed as well. Beside of SOx and NOx emissions, small particles and other pollutants (e.g. VOC, ammonia) have adverse effect on environment and human being. The natural emissions (e.g. from volcanoes) has contribution to the pollutants concentration and atmospheric chemistry governs speciation of pollutants, as in the case of secondary acidification. The methods of ambient air pollution monitoring based on modern instrumentation allow the verification of dispersion models and balancing of mass emissions. The comfort of everyday human's activity is influenced by indoor and public transport vehicles interior air contamination, which is effected even by the professional appliances operation. The outdoor pollution leads to cultural heritage objects deterioration, the mechanism are studied and the methods of rehabilitation developed. However to prevent emissions the new technologies are being developed, the new class of these technologies are plasma processes, which are briefly reviewed at the final part of the book.

Author:
Publisher:
ISBN:
Category : Air
Languages : en
Pages : 308

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