Estimating Gini Coefficient from Grouped Data Based on Shape-Preserving Cubic Hermite Interpolation of Lorenz Curve

The Lorenz curve and Gini coefficient are widely used to describe inequalities in many fields, but accurate estimation of the Gini coefficient is still difficult for grouped data with fewer groups. We proposed a shape-preserving cubic Hermite interpolation method to approximate the Lorenz curve by maximizing or minimizing the strain energy or curvature variation energy of the interpolation curve, and a method to estimate the Gini coefficient directly from the coefficients of the interpolation curve. This interpolation method can preserve the essential requirements of the Lorenz curve, i.e., non-negativity, monotonicity, and convexity, and can estimate the derivatives at intermediate points and endpoints at the same time. These methods were tested with 16 grouped quintiles or unequally spaced datasets, and the results were compared with the true Gini coefficients calculated with all census data and results estimated with other methods. Results indicate that the maximum strain energy interpolation method generally performs the best among different methods, which is applicable to both equally and unequally spaced grouped datasets with higher precision, especially for grouped data with fewer groups.

BOX DIMENSION OF A NONLINEAR FRACTAL INTERPOLATION CURVE

In this paper, we present a delightful method to estimate the lower and upper box dimensions of a special nonlinear fractal interpolation curve. We use Rakotch contractibility and monotone property of function in the estimation of upper box dimension, and we use Rakotch contractibility, noncollinearity of interpolation points, nondecreasing property of function, convex (or concave) property of function and differential mean value theorem in the estimation of lower box dimension. In particular, we propose a well-founded conjecture motivated by our results.

The Improved Trial Method of Hydrogeological Parameters Inversion by Using Single Well Recharge Formula

Based on the related theory under recharge condition, the trial method solving the hydrogeological parameters of unsteady flow by single well recharge test according to Theis Formula can be gotten. Integrating the cubic spline interpolation curve of the parameters into the said trial method, the improved trial method of inversion hydrogeological parameters is worked out by using single well recharge formula. In this method, the cubic spline interpolation curve is constructed from three groups of initial adjacent comparison points at first. Then the fussy trial process of the traditional trial method can be replaced by line-line intersection. It can be seen from the practical verification of the data of underground water manual recharge test somewhere in Xi’an City that the calculation steps here are greatly simplified comparing to the traditional trial method. And the calculation result is basically the same with the existing data, which shows that this method is simple and effective.

An Algorithm for Representing Planar Curves in B-Splines

An algorithm for representing planar curves in B-splines is presented in this paper. The representing problem is different from the approximation to data points; planar curve provided more information than data points. To make full use of the information, we propose a three-step representing approach: 1.Sample data points along with their tangent vectors from the planar curve according to the given accuracy. 2. Fit the sampled points by Bezier segments using local interpolation; compose these segments to an interpolation curve. 3. Approximate the interpolation curve using the best least approximation to get the final B-spline curve. Tangent information is used in the second step to construct the interpolation curve. In the third step, the system is always positive because of using the best least square approximation, so we can get more freedoms to approximate the interpolation curve. Finally, some examples of this algorithm demonstrate its usefulness and quality.