In many applications, the duration of an uninterrupted measurement of a time series is limited. However, it is often possible to obtain several separate segments of data. The estimation of an autoregressive model from this type of data is discussed. A straightforward approach is to take the average of models estimated from each segment separately. In this way, the variance of the estimated para...

The large variance of the Wigner Ville distribution makes smoothing essential for producing readable estimates of the time varying power spectrum of noise corrupted signals Since linear smoothing trades reduced variance for increased bias of the signal components we explore two nonlinear estimation techniques based on soft thresholding in an orthonormal basis representation Soft thresholding pr...

Background: In the last decade, adult mortality in the United States has continued its long-run decline, while diabetes prevalence has increased. It is unknown whether the additional person-years lived in the adult population have mostly been spent in a diseased or a disease-free state. Furthermore, although illness and death are stochastic processes, little is known about the variance in diabe...

Conventional selective genotyping which is using the extreme phenotypes (EP) was compared with alternative criteria to find the most informative animals for genotyping with respects to mapping quantitative trait loci (QTL). Alternative sampling strategies were based on minimizing the sampling error of the estimated QTL effect (MinERR) and maximizing likelihood ratio test (MaxLRT) using both phe...

Dominance may be an important source of non-additive genetic variance for many traits of dairy cattle. However, nearly all prediction models for dairy cattle have included only additive effects because of the limited number of cows with both genotypes and phenotypes. The role of dominance in the Holstein and Jersey breeds was investigated for eight traits: milk, fat, and protein yields; product...

the present study is an attempt toward evaluating the performance of portfolios and assets selecting using modified mean-variance models by utilizing a non-parametric efficiency analysis tool, namely data envelopment analysis (dea). huge amounts of money are being invested in financial market. as a result, portfolio performance evaluation has created a great deal of interest among people. we kn...