There is recent evidence from laboratory experiments and analysis of livestock populations that not only the phenotype itself, but also its environmental variance, is under genetic control. Little is known about the relationships between the environmental variance of one trait and mean levels of other traits, however. A genetic covariance between these is expected to lead to nonlinearity betwee...

Aims. We develop and validate tools for estimating residual noise covariance in Planck frequency maps, we also quantify signal error effects and compare different techniques to produce low-resolution maps. Methods. We derived analytical estimates of covariance of the residual noise contained in low-resolution maps produced using a number of mapmaking approaches. We tested these analytical predi...

Both chromatic and luminance-modulated stimuli are served by multiple spatial-frequency-tuned channels. This experiment investigated the independence versus interdependence of spatial frequency channels that serve the detection of red-green chromatic versus yellow-black luminance-modulated stimuli at low spatial frequencies. Contrast thresholds for both chromatic and luminance-modulated grating...

Brain structural covariance networks (SCNs) composed of regions with correlated variation are altered in neuropsychiatric disease and change with age. Little is known about the development of SCNs in early childhood, a period of rapid cortical growth. We investigated the development of structural and maturational covariance networks, including default, dorsal attention, primary visual and senso...

Many inference techniques for multivariate data analysis assume that the rows of the data matrix are realizations of independent and identically distributed random vectors. Such an assumption will be met, for example, if the rows of the data matrix are multivariate measurements on a set of independently sampled units. In the absence of an independent random sample, a relevant question is whethe...

In many statistical modeling frameworks, goodness-of-fit tests are typically administered to the estimated residuals. time series setting, whiteness of residuals is assessed using sample autocorrelation function. For models, especially those used for financial series, key assumption on that they in fact independent and not just uncorrelated. this paper, we apply auto-distance covariance functio...

In multisensor target tracking, each sensor can have its own target state estimate based on the local sensor measurements. Most existing communication networks between local trackers/sensors transmit to a fusion center the local track estimates–sometimes without any estimation error covariances, sometimes with partial covariance information and only rarely with full covariance information. In o...

The puzzle is that spreads on corporate bonds are about twice as large as can be explained by defaults, taxes and illiquidity. The higher a bond’s rating and the shorter its maturity, the greater is the puzzle. We use a large dataset of bonds to identify the relevant risk factors. Systematic factors fail to generate large spreads, regardless of whether they are conventional (market covariance, ...

The aim of this study was the effectiveness of behavioral couple’s therapy to reduce domestic violence in women substance abusers. The design of this study was experimental with pre-test, pos-ttest and fallow up with control group. The study included all couples that had referred to Cessation clinic for substance abuse in Ahvaz city that among them 20 couples were selected and randomly di...

The classiication rules of linear discriminant analysis are deened by the true mean vectors and the common covariance matrix of the populations from which the data come. As these true parameters are in general unknown, they are commonly estimated by the sample mean vector and covariance matrix of the data in a training sample randomly drawn from each population. These sample statistics are howe...