This paper studies the addition of linear constraints to Support Vector Regression when kernel is linear. Adding those into problem allows add prior knowledge on estimator obtained, such as finding positive vector, probability vector or monotone data. We prove that related optimization stays a semi-definite quadratic problem. also propose generalization Sequential Minimal Optimization algorithm...

this paper estimates the determinants of inflation in iran using a linear and non- linear regression model over the period 1959-2008. in the model specification, the conventional variables (liquidity, production and exchange rate) as well as positive and negative oil revenue shocks, monetary disequilibrium, and demand gap are considered. the results show that nonlinear time series regression mo...

in this work, removal of c. i. acid red 14 was investigated by pumice stone as a low cost adsorbent. various parameters such as initial dye solution, contact time and ph were studied. removal of dye were increased by increasing of contact time and initial dye solution and deceased by increasing of ph. three isotherm models were studied. linear and non-linear regression analyses were used for de...

This Ph.D. thesis is devoted to algorithms for two optimization problems, and their implementation. The algorithms are based on solving linear M-estimation problems. First, an algorithm for the non-linear M-estimation problem is considered. The main idea of the algorithm is to linearize the residual function in each iteration and thus calculate the iteration step by solving a linear M-estimatio...