Image registration refers to the process of finding the spatial correspondence between two or more images. This is usually done by applying a spatial transformation, computed automatic or manually, to a given image using a continuous image model computed either with interpolation or approximation methods. We show that noise induced signal variance in interpolated images differs significantly fr...

Contrary to popular belief, the method of least squares (LS) does not require that the data have normally distributed (Gaussian) error for its validity. One practically important application of LS fitting that does not involve normal data is the estimation of data variance functions (VFE) from replicate statistics. If the raw data are normal, sampling estimates s(2) of the variance sigma(2) are...

In contrast to our growing understanding of patterns of additive genetic variance in single- and multi-trait combinations, the relative contribution of nonadditive genetic variance, particularly dominance variance, to multivariate phenotypes is largely unknown. While mechanisms for the evolution of dominance genetic variance have been, and to some degree remain, subject to debate, the pervasive...

BACKGROUND In genomic models that assign an individual variance to each marker, the contribution of one marker to the posterior distribution of the marker variance is only one degree of freedom (df), which introduces many variance parameters with only little information per variance parameter. A better alternative could be to form clusters of markers with similar effects where markers in a clus...

This study aimed to investigate the between- and within-individual variability in sedentary time over seven days, using a mixed-effects location scale model. The sample comprised 686 Portuguese children (381 girls) aged 9-11 years, from 23 schools. Sedentary time was estimated by the Actigraph GT3X+ accelerometer, which was used 24 hours/day for 7 consecutive days; height, sitting height, and w...

in this paper we compared multivariate garch models toestimate value-at-risk. we used a portfolio of weekly indexesincluding tedpix, klse, xu100 during ten years. to estimatevalue-at-risk, first we estimated ccc, dcc of engle, dcc of tseand tsui, dynamic equi correlation models by oxmetrics. then,optimum lags were estimated by minimizing the information criteria.to estimate var, the models accu...

Several important forms of robotic environmental monitoring involve estimating a spatial field from comparatively few measurements. A number of researchers use linear least squares estimation techniques, frequently either the geostatistical Kriging framework or a Gaussian Process regression formulation, that provide estimates of quantities of interest at unmeasured locations. These methods enab...

One of the main objectives in meta-analysis is to estimate the overall effect size by calculating a confidence interval (CI). The usual procedure consists of assuming a standard normal distribution and a sampling variance defined as the inverse of the sum of the estimated weights of the effect sizes. But this procedure does not take into account the uncertainty due to the fact that the heteroge...