We develop an asymptotic theory for the first two sample moments of a stationary multivariate long memory process under fairly general conditions. In this theory the convergence rates and the limits ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with two-way interactions between ...

The Annals of Statistics, Vol. 19, No. 3 (Sep., 1991), pp. 1370-1402 (33 pages) Buckley and James proposed an extension of the classical least squares estimator to the censored regression model. It ...

Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the response and ...

Learn what residual standard deviation is, how to calculate it in regression analysis, and why it's crucial for measuring predictability and goodness-of-fit in data modeling.

It can be highly beneficial for companies to develop a forecast of the future values of some important metrics, such as demand for its product or variables that describe the economic climate. There ...