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...

This paper discusses some asymptotic uniform linearity results of randomly weighted empirical processes based on long range dependent random variables+ These results are subsequently used to linearize nonlinear regression quantiles in a nonlinear regression model with long range dependent errors, where the design variables can be either random or nonrandom+ These, in turn, yield the limiting be...

We quantified the potential increase in accuracy of expected breeding value for weights of Nelore cattle, from birth to mature age, using multi-trait and random regression models on Legendre polynomials and B-spline functions. A total of 87,712 weight records from 8144 females were used, recorded every three months from birth to mature age from the Nelore Brazil Program. For random regression a...

genetic parameters were estimated for somatic cell score (scs) in dairy cattle of iran using test day records. the records of first lactation were extracted from the database of national animal breeding center for cows calved between 2001 and 2010. data included 222923 test-day records, obtained from 29668 animals distributed in 100 different herds. estimates were carried out through gibbs samp...

in this investigation 13699 data related to milk production from 2716 holstein first calving and daughter from 167 sire cows were analyzed based on random regression model (rr/cf) and reml method incomplete lactating (5-90 days) and (5-120 days) in correlations to complete lactating were 0.67 and 0.72, respectively with progress in complete 5-240 day was 0.91 the correlation value for lactating...

This study proposes an optimized random forest regression model to achieve online battery prognostics and health management. To estimate the state of (SOH), two aging features (AFs) are extracted based on incremental capacity curve (ICC) quantify degradation, further analyzed through Pearson’s correlation coefficient. predict remaining useful life (RUL), AFs extrapolated degradation trends clos...

This paper focuses on studying a random effects semiparametric regression model (RESPRM) with separable space-time filters. The cannot only capture the linearity and nonlinearity existing in dataset, but also avoid inefficient estimators caused by ignoring spatial correlation serial error term of data model. Its profile quasi-maximum likelihood (PQMLE) for parameters nonparametric functions, ge...