Centile estimation for a proportion response variable |
| |
Authors: | Abu Hossain Robert Rigby Mikis Stasinopoulos Marco Enea |
| |
Institution: | 1. STORM, London Metropolitan University, London, U.K.;2. University of Palermo, Palermo, Italy |
| |
Abstract: | This paper introduces two general models for computing centiles when the response variable Y can take values between 0 and 1, inclusive of 0 or 1. The models developed are more flexible alternatives to the beta inflated distribution. The first proposed model employs a flexible four parameter logit skew Student t ( logitSST ) distribution to model the response variable Y on the unit interval (0, 1), excluding 0 and 1. This model is then extended to the inflated logitSST distribution for Y on the unit interval, including 1. The second model developed in this paper is a generalised Tobit model for Y on the unit interval, including 1. Applying these two models to (1‐Y) rather than Y enables modelling of Y on the unit interval including 0 rather than 1. An application of the new models to real data shows that they can provide superior fits. Copyright © 2015 John Wiley & Sons, Ltd. |
| |
Keywords: | beta inflated distribution fractional data GAMLSS generalised Tobit model logit skew Student t distribution |
|
|