We use a basic stationary and isotropic spatial linear regression model to fit a rainfall dataset collected in central Venezuela. First order and partial second order trend explain the mean function. With a Matérn correlation function with smoothness fixed at one, unknown parameters are estimated through MCMC method. The variogram is also estimated based on the posterior samples. By examining p...

A linear model for repeated measurements is proposed in which the correlation structure within each time sequence of measurements includes parameters for measurement error, variation between experimental units, and serial correlation within units. An approach to data analysis is presented which involves preliminary analysis by ordinary least squares, use of the empirical semi-variogram of resid...

A simple collimation technique based on measuring the period of one self-image produced by a diffraction grating is proposed. Transversal displacement of the grating is not required, and then automatic single-frame processing can be performed. The self-image is acquired with a CMOS camera, and the period is computed using the variogram function. Analytical and experimental results are obtained,...

Proper scoring rules provide a theoretically principled framework for the quantitative assessment of the predictive performance of probabilistic forecasts. While a wide selection of such scoring rules for univariate quantities exists, there are only few scoring rules for multivariate quantities, and many of them require that forecasts are given in the form of a probability density function. The...