Estimation of time-varying regression model constrained at each time moment by linear inequalities is a natural statistical formulation of a wide class of nonstationary signal processing problems. The presence of linear constraints turns the originally quadratic three-diagonal problem of minimizing the residual squares sum, which is solvable by the linear Kalman-Bucy filtration-smoothing proced...

The selection of an adequate regression model is the basis for obtaining accurate and reproducible results during the bionalytical method validation. Given the wide concentration range, frequently present in bioanalytical assays, heteroscedasticity of the data may be expected. Several weighted linear and quadratic regression models were evaluated during the selection of the adequate curve fit u...

The use of regression analysis has been instrumental in allowing evolutionary biologists to estimate the strength and mode of natural selection. Although directional and correlational selection gradients are equal to their corresponding regression coefficients, quadratic regression coefficients must be doubled to estimate stabilizing/disruptive selection gradients. Based on a sample of 33 paper...

A pedigree file consisting of 5860 individuals, 167 sires and 1582 dams collected at Makooei sheep breeding station (MSBS) during a period of 24 years (1990 to 2013) was used to calculate the inbreeding coefficients to reveal any probable effects of inbreeding (F) on the studied traits. The studied traits were classified to the five main groups including body weight, Kleiber ratio, body measure...

Support Vector Regression (SVR) solves regression problems based on the concept of Support Vector Machine (SVM). In this paper, a new model of SVR with probabilistic constraints is proposed that any of output data and bias are considered the random variables with uniform probability functions. Using the new proposed method, the optimal hyperplane regression can be obtained by solving a quadrati...