The adjusted r-squared is helpful for multiple regression and corrects for erroneous regression, giving you a more accurate ...

Many response variables are handled poorly by regression models when the errors are assumed to be normally distributed. For example, modeling the state damaged/not damaged of cells after treated with ...

Scandinavian Journal of Statistics, Vol. 43, No. 4 (December 2016), pp. 1035-1045 (11 pages) Linear structural equation models, which relate random variables via linear inter-dependencies and Gaussian ...

In the early 1970s, statisticians had difficulty in analysing data where the random variation of the errors did not come from the bell-shaped normal distribution. Besides normality, these traditional ...

This is a preview. Log in through your library . Abstract We consider the semi-parametric regression model Y = X t β + Φ(Z) where β and Φ(·) are unknown slope coefficient vector and function, and ...