SNOMAD is a collection of algorithms for the normalization and standardization of gene expression datasets derived from diverse biological and technological sources. In addition to conventional transformations and visualization tools, SNOMAD includes two non-linear transformations which correct for bias and variance which are non-uniformly distributed across the range of microarray element sign...

We define a nonparametric prewhitening method for estimating conditional quantiles based on local linear quantile regression. We characterize the bias, variance and asymptotic normality of the proposed estimator. Under weak conditions our estimator can achieve bias reduction and have the same variance as the local linear quantile estimators. A small set of Monte Carlo simulations is carried out...

Question: Previous interpretations of the variance plot of paired quadrat variance method (PQV) have been incomplete. The objective of this study was to clarify the interpretation of PQV, and to shed additional light on how different quadrat variance methods can be used, in concert, to measure scale in transect data. Methods: We used artificial and real data to examine how the PQV method elucid...

rangelands are the main sources of forage for livestock feeding by localpeople. beside forage production, rangeland ecosystems provide many other goods andservices such as medicinal plants, recreation, soil and water conservation, wildlife habitat,fishing, hunting, hiking, etc. nevertheless, there are no much information about the waythat local communities think about the rangelands goods and s...

Local measurements of the Hubble expansion rate are affected by structures like galaxy clusters or voids. Here we present a fully relativistic treatment of this effect, studying how clustering modifies the dispersion of the mean distance (modulus)-redshift relation in a standard ΛCDM universe. Our findings is that cosmic variance (i.e. the effects of the local structure) is, for supernova obser...

The problem of matching feature points in multiple images is difficult to solve when their appearance changes due to illumination variance, either by lighting or object motion. In this paper we tackle this ill-posed problem by using the difference of local phase which is known to be stable to a certain extent even under illumination variances. In order to realize a precise matching, we basicall...

Questions concerning the properties and quantification of density fluctuations in point patterns continue to provide many theoretical challenges. The purpose of this paper is to characterize certain fundamental aspects of local density fluctuations associated with general point patterns in any space dimension d. Our specific objectives are to study the variance in the number of points contained...

We introduce $k$-variance, a generalization of variance built on the machinery random bipartite matchings. $K$-variance measures expected cost matching two sets $k$ samples from distribution to each other, capturing local rather than global information about measure as increases; it is easily approximated stochastically using sampling and linear programming. In addition defining $k$-variance pr...

Questions concerning the properties and quantification of density fluctuations in point patterns continues to provide many theoretical challenges. The purpose of this paper is to characterize certain fundamental aspects of local density fluctuations associated with general point patterns in any space dimension d. Our specific objectives are to study the variance in the number of points containe...