Variable Selection in Nonparametric Classification via Measurement Error Model Selection Likelihoods

Using the relationships among ridge regression, LASSO estimation, and measurement error attenuation as motivation, a new measurement-error-model-based approach to variable selection is developed. After describing the approach in the familiar context of linear regression, we apply it to the problem of variable selection in nonparametric classification, resulting in a new kernel-based classifier with LASSO-like shrinkage and variable-selection properties. Finite-sample performance of the new classification method is studied via simulation and real data examples, and consistency of the method is studied theoretically. Supplementary materials for the paper are available online.

Characterizing ammonia emissions from swine farms in eastern North Carolina: part 1--conventional lagoon and spray technology for waste treatment

Ammonia (NH3) fluxes from waste treatment lagoons and barns at two conventional swine farms in eastern North Carolina were measured. The waste treatment lagoon data were analyzed to elucidate the temporal (seasonal and diurnal) variability and to derive regression relationships between NH3 flux and lagoon temperature, pH and ammonium content of the lagoon, and the most relevant meteorological parameters. NH3 fluxes were measured at various sampling locations on the lagoons by a flowthrough dynamic chamber system interfaced to an environmentally controlled mobile laboratory. Two sets of open-path Fourier transform infrared (FTIR) spectrometers were also used to measure NH3 concentrations for estimating NH3 emissions from the animal housing units (barns) at the lagoon and spray technology (LST) sites. Two different types of ventilation systems were used at the two farms. Moore farm used fan ventilation, and Stokes farm used natural ventilation. The early fall and winter season intensive measurement campaigns were conducted during September 9 to October 11, 2002 (lagoon temperature ranged from 21.2 to 33.6 degrees C) and January 6 to February 2, 2003 (lagoon temperature ranged from 1.7 to 12 degrees C), respectively. Significant differences in seasonal NH3 fluxes from the waste treatment lagoons were found at both farms. Typical diurnal variation of NH3 flux with its maximum value in the afternoon was observed during both experimental periods. Exponentially increasing flux with increasing surface lagoon temperature was observed, and a linear regression relationship between logarithm of NH3 flux and lagoon surface temperature (T1) was obtained. Correlations between lagoon NH3 flux and chemical parameters, such as pH, total Kjeldahl nitrogen (TKN), and total ammoniacal nitrogen (TAN) were found to be statistically insignificant or weak. In addition to lagoon surface temperature, the difference (D) between air temperature and the lagoon surface temperature was also found to influence the NH3 flux, especially when D > 0 (i.e., air hotter than lagoon). This hot-air effect is included in the statistical-observational model obtained in this study, which was used further in the companion study (Part II), to compare the emissions from potential environmental superior technologies to evaluate the effectiveness of each technology.

Characterizing ammonia emissions from swine farms in eastern North Carolina: part 2--potential environmentally superior technologies for waste treatment

The need for developing environmentally superior and sustainable solutions for managing the animal waste at commercial swine farms in eastern North Carolina has been recognized in recent years. Program OPEN (Odor, Pathogens, and Emissions of Nitrogen), funded by the North Carolina State University Animal and Poultry Waste Management Center (APWMC), was initiated and charged with the evaluation of potential environmentally superior technologies (ESTs) that have been developed and implemented at selected swine farms or facilities. The OPEN program has demonstrated the effectiveness of a new paradigm for policy-relevant environmental research related to North Carolina's animal waste management programs. This new paradigm is based on a commitment to improve scientific understanding associated with a wide array of environmental issues (i.e., issues related to the movement of N from animal waste into air, water, and soil media; the transmission of odor and odorants; disease-transmitting vectors; and airborne pathogens). The primary focus of this paper is on emissions of ammonia (NH3) from some potential ESTs that were being evaluated at full-scale swine facilities. During 2-week-long periods in two different seasons (warm and cold), NH3 fluxes from water-holding structures and NH3 emissions from animal houses or barns were measured at six potential EST sites: (1) Barham farm--in-ground ambient temperature anaerobic digester/energy recovery/greenhouse vegetable production system; (2) BOC #93 farm--upflow biofiltration system--EKOKAN; (3) Carrolls farm--aerobic blanket system--ISSUES-ABS; (4) Corbett #1 farm--solids separation/ gasification for energy and ash recovery centralized system--BEST; (5) Corbett #2 farm--solid separation/ reciprocating water technology--ReCip; and (6) Vestal farm--Recycling of Nutrient, Energy and Water System--ISSUES-RENEW. The ESTs were compared with similar measurements made at two conventional lagoon and spray technology (LST) farms (Moore farm and Stokes farm). A flow-through dynamic chamber system and two sets of open-path Fourier transform infrared (OP-FTIR) spectrometers measured NH3 fluxes continuously from water-holding structures and emissions from housing units at the EST and conventional LST sites. A statistical-observational model for lagoon NH3 flux was developed using a multiple linear regression analysis of 15-min averaged NH3 flux data against the relevant environmental parameters measured at the two conventional farms during two different seasons of the year. This was used to compare the water-holding structures at ESTs with those from lagoons at conventional sites under similar environmental conditions. Percentage reductions in NH3 emissions from different components of each potential EST, as well as the whole farm on which the EST was located were evaluated from the estimated emissions from water-holding structures, barns, etc., all normalized by the appropriate nitrogen excretion rate at the potential EST farm, as well as from the appropriate conventional farm. This study showed that ammonia emissions were reduced by all but one potential EST for both experimental periods. However, on the basis of our evaluation results and analysis and available information in the scientific literature, the evaluated alternative technologies may require additional technical modifications to be qualified as unconditional ESTs relative to NH3 emissions reductions.

Measurement error, instrumental variables and corrections for attenuation with applications to meta-analyses

MacMahon et al. present a meta-analysis of the effect of blood pressure on coronary heart disease, as well as new methods for estimation in measurement error models for the case when a replicate or second measurement is made of the fallible predictor. The correction for attenuation used by these authors is compared to others already existing in the literature, as well as to a new instrumental variable method. The assumptions justifying the various methods are examined and their efficiencies are studied via simulation. Compared to the methods we discuss, the method of MacMahon et al. may have bias in some circumstances because it does not take into account: (i) possible correlations among the predictors within a study; (ii) possible bias in the second measurement; or (iii) possibly differing marginal distributions of the predictors or measurement errors across studies. A unifying asymptotic theory using estimating equations is also presented.

A measurement-error model for binary and ordinal regression

Exposure assessment poses special problems in air pollution epidemiology. This paper proposes a probit regression model for binary and ordinal outcomes that uses exposure validation information to develop estimates for the coefficient of the true exposure when only the inaccurate 'surrogate' measure of exposure is available for the individuals in the health study. This method is closely related to recently developed measurement-error methods, and is based on the assumption that the outcome and the surrogate exposure are conditionally independent given the true exposure. A test statistic is proposed for checking this conditional independence assumption when more than one surrogate is available, and an interpretation of the coefficient estimate is provided in the event that the assumption is violated. The methods are applied to an example involving nitrogen dioxide exposure and wheeze in children.