Measuring inequality: application of semi-parametric methods to real life data

Semi-parametric Methods for Longitudinal Data Analysis

Self-modeling regression is a powerful semi-parametric tool for analysis of longitudinal data with time-invariant covariates. This paper explores the use of self-modelling regression for tting data from a designed experiment in which the response is a curve. Recent advances in mixed nonlinear models and nonparametric regression with time series errors has made the use of mixed model self-modeli...

Penalized Lasso Methods in Health Data: application to trauma and influenza data of Kerman

Background: Two main issues that challenge model building are number of Events Per Variable and multicollinearity among exploratory variables. Our aim is to review statistical methods that tackle these issues with emphasize on penalized Lasso regression model.  The present study aimed to explain problems of traditional regressions due to small sample size and m...

Semi-parametric and Parametric Methods for the Analysis of Multi-center Survival Data

Measuring inequality with interval data

This paper employs the axiomatic approach underpinning the literature on income inequality measurement to analyze measures of dispersion in interval data. We …nd that some widely employed measures fail to properly measure dispersion when data are not of the ratio type. We go on to prove that, under reasonable conditions, variance is the only decomposable measure that can be used to consistently...

Hölder continuity of a parametric variational inequality

‎In this paper‎, ‎we study the Hölder continuity of solution mapping to a parametric variational inequality‎. ‎At first‎, ‎recalling a real-valued gap function of the problem‎, ‎we discuss the Lipschitz continuity of the gap function‎. ‎Then under the strong monotonicity‎, ‎we establish the Hölder continuity of the single-valued solution mapping for the problem‎. ‎Finally‎, ‎we apply these resu...