arXiv subjects

James V Zidek

Publications and source records attributed to James V Zidek.

3 recordsLinked to original sources

arXiv2023

Preferential monitoring site location in the Southern California Air Quality Basin

The preferential siting of the locations of monitors of hazardous environmental fields can lead to the serious underestimation of the impacts of those fields. In particular, human health effects can be severely underestimated when standard statistical are applied without appropriate adjustment. This report describes an extensive analysis of the siting of monitors for a network that measures air pollution PM10 in California's South Coast Air Basin SOCAB. That analysis uses EPA data collected during the 1986 to 2019 period. Background descriptions, including those published by the US EPA are provided. The analysis uses a very general and fast Monte Carlo test for preferential sampling developed by Dr Joe Watson, which confirms that the sites were preferentially sited, as would be expected, given the intended purpose of the network to detect noncompliance with air quality standards. Our findings demonstrate both the value of that algorithm for application where where such background knowledge is not available, and hence to situations in which standard statistical tools require modification.

stat.AP↗

arXiv2011

Modeling Non-Stationary Processes Through Dimension Expansion

In this paper, we propose a novel approach to modeling nonstationary spatial fields. The proposed method works by expanding the geographic plane over which these processes evolve into higher dimensional spaces, transforming and clarifying complex patterns in the physical plane. By combining aspects of multi-dimensional scaling, group lasso, and latent variables models, a dimensionally sparse projection is found in which the originally nonstationary field exhibits stationarity. Following a comparison with existing methods in a simulated environment, dimension expansion is studied on a classic test-bed data set historically used to study nonstationary models. Following this, we explore the use of dimension expansion in modeling air pollution in the United Kingdom, a process known to be strongly influenced by rural/urban effects, amongst others, which gives rise to a nonstationary field.

stat.ME↗

arXiv2007

Modeling Hourly Ozone Concentration Fields

This paper presents a dynamic linear model for modeling hourly ozone concentrations over the eastern United States. That model, which is developed within an Bayesian hierarchical framework, inherits the important feature of such models that its coefficients, treated as states of the process, can change with time. Thus the model includes a time--varying site invariant mean field as well as time varying coefficients for 24 and 12 diurnal cycle components. This cost of this model's great flexibility comes at the cost of computational complexity, forcing us to use an MCMC approach and to restrict application of our model domain to a small number of monitoring sites. We critically assess this model and discover some of its weaknesses in this type of application.

stat.AP↗