When the data collected or the experiment conducted is under ideal conditions, well-known statistical model may give a better fit. But when the situations are not ideal due to presence of some distorting factors, standard model may not give a good fit for the data set. One possible method to take an account of this distorting factor is to modify the existing model.
In this article we generate class of density functions by using contour transformations that depends on a slant parameter. Let f be a unimodel density function with modal value zero. We obtain new density function f* by transforming the contours C(u) of f such that the center of each transformed contours C*(u) is on the line segment joining the origin and (β, f (0)). As an illustration slanted Normal and slanted Laplace densities are obtained. A method to generate a random sample from slanted density is discussed and we study the performance of the slant parameter β.
Unimodal, Symmetric, Contour density,
