Let $X_{1},X_{2},\ldots ,X_{n}$ be independent random variables. Given the moments $EX_{j}^{s}$ (s = 1, 2,...,m), (j = 1, 2,...,n), the joint distribution function of ...

We present sharp tail asymptotics for the density and the distribution function of linear combinations of correlated log-normal random variables, that is, exponentials of components of a correlated ...

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

This section provides an overview of a likelihood-based approach to general linear mixed models. This approach simplifies and unifies many common statistical analyses, including those involving ...

If the model is not full rank, there are an infinite number of least-squares solutions for the estimates. PROC REG chooses a nonzero solution for all variables that are linearly independent of ...