This paper has elaborated upon the deleterious effects of outliers and corruption of dataset on estimation of linear regression coefficients by the Ordinary Least Squares method. Motivated to ameliorate the estimation procedure, we have introduced the robust regression estimators based on...

Johan Gielis showed that all closed curves might be considered as some sort of deformed ellipses. He gave a superformula to parameterize such shapes. In this study an attempt has been made to estimate the parameters of Gielis' superformula from empirical data. We use an optimum search algorithm...

Ricardo Chacoacute;n generalized Johan Gielis's superformula by introducing elliptic functions in place of trigonometric functions. In this paper an attempt has been made to fit the Chacoacute;n-Gielis curves (modified by various functions) to simulated data. Estimation has been done by the...

This short note proposes working out of the standard errors of estimate of composite indices when they are constructed by using intrinsically derived weights. It illustrates the proposed method, using the jackknife re-sampling technique, by an example that relates to crime of different types in...

The Two-Stage Least squares method for obtaining the estimated structural coefficients of a simultaneous linear equations model is a celebrated method that uses OLS at the first stage for estimating the reduced form coefficients and obtaining the expected values in the arrays of current...

In the economics of joint production one often distinguishes between the two cases: the one in which a firm produces multiple products each produced under separate production process, and the other "true joint production" where a number of outputs are produced from a single production process,...

Some signal waveforms are very fast dampening oscillatory time series composed of exponential functions. The regular least squares fitting techniques are often unstable when used to fit exponential functions to such signal waveforms since such functions are highly correlated. Of late, some...

No fool-proof method exists to fit nonlinear curves to data or estimate the parameters of an intrinsically nonlinear function. Some methods succeed at solving a set of problems but fail at the others. The Differential Evolution (DE) method of global optimization is an upcoming method that has...

In this paper an attempt has been made to estimate the parameters of Gielis superformula (modified by various functions). Simulated data have been used for this purpose. The estimation has been done by the method of simulated annealing. It has been found that the simulated annealing method is...

A high degree of multicollinearity among the explanatory variables severely impairs estimation of regression coefficients by the Ordinary Least Squares. Several methods have been suggested to ameliorate the deleterious effects of multicollinearity. In this paper we aim at comparing the...