A coupled Bayesian model selection and geostatistical regression modeling approach is adopted for empirical analysis of gross primary productivity (GPP) at six AmeriFlux sites, including the Kennedy Space Center Scrub Oak, Vaira Ranch, Tonzi Ranch, Blodgett Forest, Morgan Monroe State Forest, and Harvard Forest sites. The analysis is performed at a continuum of temporal scales ranging from dail...

BACKGROUND Modelling the environmental niche and spatial distribution of pathogen-transmitting arthropods involves various quality and methodological concerns related to using climate data to capture the environmental niche. This study tested the potential of MODIS remotely sensed and interpolated gridded covariates to estimate the climate niche of the medically important ticks Ixodes ricinus a...

Consistent maximum-likelihood heritability estimates of consumption of alcoholic beverages were observed at three separate times during a 14- to 18-year period in adult twin males initially aged 42-56 years in 1969-1973. Log transformation of the average number of drinks/week of the returnees to all three examinations was examined relative to potential covariates representing both antecedents o...

BACKGROUND Platelet aggregation plays an important role in arterial thrombosis in coronary heart disease, stroke, and peripheral arterial disease. However, the contribution of genetic versus environmental influences on interindividual variation in platelet aggregability is poorly characterized. METHODS AND RESULTS We studied the heritability of platelet aggregation responses in 2413 participa...

Collecting environmental DNA (eDNA) as a nonlethal sampling approach has been valuable in detecting the presence/absence of many imperiled taxa; however, its application to indicate species abundance poses challenges. A deeper understanding eDNA dynamics aquatic systems is required better interpret substantial variability often associated with samples. Our design took advantage natural variatio...

This paper studies the ordered weighted `1 (OWL) family of regularizers for sparse linear regression with strongly correlated covariates. We prove sufficient conditions for clustering correlated covariates, extending and qualitatively strengthening previous results for a particular member of the OWL family: OSCAR (octagonal shrinkage and clustering algorithm for regression). We derive error bou...

This paper studies the ordered weighted `1 (OWL) family of regularizers for sparse linear regression with strongly correlated covariates. We prove sufficient conditions for clustering correlated covariates, extending and qualitatively strengthening previous results for a particular member of the OWL family: OSCAR (octagonal shrinkage and clustering algorithm for regression). We derive error bou...

In this article we consider the stochastic restricted ridge estimation in semipara-metric linear models when the covariates are measured with additive errors. The development of penalized corrected likelihood method in such model is the basis for derivation of ridge estimates. The asymptotic normality of the resulting estimates are established. Also, necessary and sufficient condition...