We present a methodology to perform spatial prediction when measured data are curves. In particular, we propose both an estimator of the spatial correlation and a functional kriging predictor. We adapt an optimization criterium used in multivariable spatial prediction in order to estimate the kriging parameters. A real data example on soil penetration resistences illustrates our proposals.

Chaotic particle swarm optimization (CPSO) algorithm is proposed to optimize the Kriging model, which can improve the precision of curve fitting. A typical example is selected to demonstrate the advantage of the optimized Kriging model, compared with other curve fitting tools.

Nonlinear constrained optimization algorithms are widely utilized in artifact design. Certain algorithms also lend themselves well to design of experiments (DOE). Adaptive design refers to experimental design where determining where to sample next is influenced by information from previous experiments. We present a constrained optimization algorithm known as superEGO (a variant of the EGO algor...

Consider repeated measures data with many zeros. For the case with one grouping factor and one repeated measure, we examine several models, assuming that the nonzero data are roughly lognormal. One of the simplest approaches is to model the zeros as left-censored observations from the lognormal distribution. A random effect is assumed for subjects. The censored model makes a strong assumption a...

MOTIVATION Distribution analysis is one of the most basic forms of statistical analysis. Thanks to improved analytical methods, accurate and extensive quantitative measurements can now be made of the mRNA, protein and metabolite from biological systems. Here, we report a large-scale analysis of the population abundance distributions of the transcriptomes, proteomes and metabolomes from varied b...

The method of stochastic simulation is proposed to model the atmospheric effect on InSAR measurements based on sample data. Test results show that 37.44% reduction in the standard devisation of the atmospheric errors can be achieved with the method of stochastic simulation, compared to 25.69% with the method of Kriging interpolator. The relative improvement of the former over the latter amounts...

Risk stratification is most directly and informatively summarized as a risk distribution curve. From this curve the ROC curve, predictiveness curve, and other curves depicting risk stratification can be derived, demonstrating that they present similar information. A mathematical expression for the ROC curve AUC is derived which clarifies how this measure of discrimination quantifies the overlap...

drought monitoring is a fundamental component of drought risk management. it is normally performed usingvarious drought indices that are effectively continuous functions of rainfall and other hydrometeorological variables.in many instances, drought indices are used for monitoring purposes. geostatistical methods allow the interpolationof spatially referenced data and the prediction of values fo...

Accurate mapping of total soil C on the field scale is essential for evaluating efforts to sequester soil C and for providing individual producers with information on C sequestration potentials of their fields. Data on easily measured secondary variables that are strongly related to soil C are believed to be helpful in improving mapping accuracy. The objective of this study was to assess improv...