Dimitris Politis
Contributing Editor Dimitris Politis writes: Consider the standard setup where $X_1,\ldots, X_n$ are i.i.d. from distribution $F$ with mean $\mu=EX_i$, variance $\sigma^2=E(X_i-\mu)^2>0$, skewness $\gamma = E(X_i-\mu)^3/\sigma^3$, and kurtosis $\kappa = E(X_i-\mu)^4/\sigma^4$ assumed finite. As usual, define the sample mean $\bar X=\frac{1}{n}\sum_{i=1}^n X_i$, the sample variance \$\hat \sigma^2=\frac{1}{n-1}\sum_{i=1}^n (X_i…

Dimitris Politis is a professor in the Department of Mathematics at the University of California in San Diego. He is one of the IMS Bulletin’s Contributing Editors, and a former Editor (January 2011–December 2013). Here, he writes about his most recent pastime, Model-Free Prediction: 1. Estimation Parametric models served as…