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 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 ...

It has long been known that insufficient consideration of spatial autocorrelation leads to unreliable hypothesis-tests and inaccurate parameter estimates. Yet, ecologists are confronted with a ...