A Nonlinear Least Squares Fit procedure for analysis of immittance data of electrochemical systems

The least squares fit of a hyperplane to uncertain data

Least Squares Smoothing of Nonlinear Systems

We consider the fixed interval smoothing problem for data from linear or nonlinear models where there is a priori information about the boundary values of the state process. The nonlinearities and boundary values preclude a stochastic approach so instead we use a least squares methodology. The resulting variational equations are a coupled system of ordinary differential equations for the state ...

Superlinearly convergent exact penalty projected structured Hessian updating schemes for constrained nonlinear least squares: asymptotic analysis

We present a structured algorithm for solving constrained nonlinear least squares problems, and establish its local two-step Q-superlinear convergence. The approach is based on an adaptive structured scheme due to Mahdavi-Amiri and Bartels of the exact penalty method of Coleman and Conn for nonlinearly constrained optimization problems. The structured adaptation also makes use of the ideas of N...

a time-series analysis of the demand for life insurance in iran

با توجه به تجزیه و تحلیل داده ها ما دریافتیم که سطح درامد و تعداد نمایندگیها باتقاضای بیمه عمر رابطه مستقیم دارند و نرخ بهره و بار تکفل با تقاضای بیمه عمر رابطه عکس دارند

Unifying Least Squares, Total Least Squares and Data Least Squares

The standard approaches to solving overdetermined linear systems Ax ≈ b construct minimal corrections to the vector b and/or the matrix A such that the corrected system is compatible. In ordinary least squares (LS) the correction is restricted to b, while in data least squares (DLS) it is restricted to A. In scaled total least squares (Scaled TLS) [15], corrections to both b and A are allowed, ...