Fast Function Extraction (FFX) is a deterministic algorithm for solving symbolic regression problems. We improve the accuracy of FFX by adding parameters to arguments nonlinear functions. Instead only optimizing linear parameters, we optimize these additional with separable least squared optimization using variable projection algorithm. Both and our new applied on PennML benchmark suite. show t...

Article history: Received 7 August 2014 Received in revised form 20 June 2015 Accepted 29 June 2015 Available online 9 July 2015 This study investigates whether a firm with strong corporate governance (CG) requires political connections (PCs), that is, we examine whether CG and PC substitute for or complement each other. Using 71,069 individual bank loan contracts from Taiwan, we examine how lo...

from the political sociology point of view, emerging and continuity of modern societies have been a combined with some kind of totalitarianism in west (as the first step of development), modern nation-states, modern revolutions, modern wars, formation of totalitarian communism-fashism, democratic systems, and at least globalization, terrorism, …. terrorism phenomena has been deep in glomming be...

This article introduces the use of regression models based on the Poisson distribution as a tool for resolving common problems in analyzing aggregate crime rates. When the population size of an aggregate unit is small relative to the offense rate, crime rates must be computed from a small number of offenses. Such data are ill-suited to least-squares analysis. Poisson-based regression models of ...

We study the convergence of discrete and penalized least squares spherical splines in spaces with stable local bases. We derive a bound for error in the approximation of a sufficiently smooth function by the discrete and penalized least squares splines. The error bound for the discrete least squares splines is explicitly dependent on the mesh size of the underlying triangulation. The error boun...

A function based nonlinear least squares estimation (FNLSE) method is proposed and investigated in parameter estimation of Jelinski–Moranda software reliability model. FNLSE extends the potential fitting functions of traditional least squares estimation (LSE), and takes the logarithm transformed nonlinear least squares estimation (LogLSE) as a special case. A novel power transformation function...

in this paper, some applications of the method of least squares (mls) for the solution of various problems in electromagnetics engineering is briefly reviewed. here, mls is employed for the solution of various problems such as solution of equations, curve fitting to measured data, generalized fourier coefficients, linear operator equations, inegro-differential equations, electrostatics and magn...