Multivariate simulations of a set of random variables are often needed for risk analysis. Given a historical data set, the goal is to develop simulations that reproduce the dependence structure in that data set so that the risk of potentially correlated factors can be evaluated. A nonparametric, copula-based simulation approach is developed and exemplified. It can be applied to multiple variabl...

This paper compares various nonparametric models for the estimation of farm specific marginal costs function in the dairy sector. Specifically, locally weighted regression approaches using theory-consistent cost function frameworks as polynomials in the nonparametric approach are applied. A comparison of average marginal cost levels as well as marginal cost distributions across farms illustrate...

Title of Dissertation: Nonparametric Quasi-likelihood in Longitudinal Data Analysis Xiaoping Jiang, Doctor of Philosophy, 2004 Dissertation directed by: Professor Paul J. Smith Statistics Program Department of Mathematics This dissertation proposes a nonparametric quasi-likelihood approach to estimate regression coefficients in the class of generalized linear regression models for longitudinal ...

In this article, we introduce two community-contributed data envelopment analysis commands for measuring technical efficiency and productivity change in Stata. Over the last decades, an important theoretical progression of analysis, a nonparametric method widely used to assess performance decision-making units, is incorporation undesirable outputs. Models able deal with outputs have been develo...