Linear regression is a type of data analysis that considers the linear relationship between a dependent variable and one or more independent variables. It is typically used to visually show the ...

THE “simplified” method of calculating a linear regression put forward by Aldridge, Berry and Davies 1 is the well-known method of orthogonal polynomials which was put on a practical working basis by ...

Statistical texts written by geographers invariably illustrate and calculate the prediction limits about an estimated regression line as pairs of parallel lines. Such limits should be hyperbolic when ...

Ordinary linear regression (OLR) assumes that response variables are continuous. Generalized Linear Models (GLMs) provide an extension to OLR since response variables can be continuous or discrete ...

In this paper we introduce a smooth version of local linear regression estimators and address their advantages. The MSE and MISE of the estimators are computed explicitly. It turns out that the local ...

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 ...