Groundwater levels across parts of western Kansas have been declining at unsustainable rates due to pumping for agricultural irrigation despite water-saving efforts. Accelerating this decline is the complex landscape, consisting both categorical (e.g., management boundaries) and numerical crop prices) factors that drive decisions, making integrated water budget a challenge. Furthermore, these f...

Propensity score weighting is sensitive to model misspecification and outlying weights that can unduly influence results. The authors investigated whether trimming large weights downward can improve the performance of propensity score weighting and whether the benefits of trimming differ by propensity score estimation method. In a simulation study, the authors examined the performance of weight...

Recurrence data arise from multi-disciplinary domains spanning reliability, cyber security, healthcare, online retailing, etc. This paper investigates an additive-tree-based approach, known as Boost-R (Boosting for Data), recurrent event with both static and dynamic features. constructs ensemble of gradient boosted additive trees to estimate the cumulative intensity function process, where a ne...

Propensity score applications are often used to evaluate educational program impact. However, various options are available to estimate both propensity scores and construct comparison groups. This study used a student achievement dataset with commonly available covariates to compare different propensity scoring estimation methods (logistic regression, boosted regression, and Bayesian logistic r...

In ecology, as in other research fields, efficient sampling for population estimation often drives sample designs toward unequal probability sampling, such as in stratified sampling. Design based statistical analysis tools are appropriate for seamless integration of sample design into the statistical analysis. However, it is also common and necessary, after a sampling design has been implemente...

Tropical forests are significant carbon sinks and their soils' carbon storage potential is immense. However, little is known about the soil organic carbon (SOC) stocks of tropical mountain areas whose complex soil-landscape and difficult accessibility pose a challenge to spatial analysis. The choice of methodology for spatial prediction is of high importance to improve the expected poor model r...

Quantifying soil pH at manifold spatio-temporal scales is critical for examining the impacts of global change on quality. It still unclear whether meteorological data and normalized difference vegetation index (NDVI) can be used to quantify in grasslands. Here, nine methods (i.e., RF: random-forest, GLR: generalized-linear-regression, GBR: generalized-boosted-regression, MLR: multiple-linear-re...