Ordinary regression analysis is based on several statistical assumptions. One key assumption is that the errors are independent of each other. However, with time series data, the ordinary regression ...

The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 22, No. 2 (Jun., 1994), pp. 219-231 (13 pages) We consider the problem of robust M-estimation of a vector of regression ...

This repository contains a single Stata do-file that implements a full suite of diagnostic tests and remedies for violations of the classical linear regression assumptions in cross-sectional data: ...

The regression model with autocorrelated disturbances is as follows: In these equations, y t are the dependent values, x t is a column vector of regressor variables, is a column vector of structural ...

This is the twelfth in a series of lecture notes which, if tied together into a textbook, might be entitled “Practical Regression.” The purpose of the notes is to supplement the theoretical content of ...

Asymptotic theory for heteroskedasticity autocorrelation consistent (HAC) covariance matrix estimators requires the truncation lag, or bandwidth, to increase more slowly than the sample size. This ...

Will Kenton is an expert on the economy and investing laws and regulations. He previously held senior editorial roles at Investopedia and Kapitall Wire and holds a MA in Economics from The New School ...