English

Confidence Bands for the Logistic and Probit Regression Models Over Intervals

Statistics Theory 2016-04-06 v1 Methodology Statistics Theory

Abstract

This article presents methods for the construction of two-sided and one-sided simultaneous hyperbolic bands for the logistic and probit regression models when the predictor variable is restricted to a given interval. The bands are constructed based on the asymptotic properties of the maximum likelihood estimators. Past articles have considered building two-sided asymptotic confidence bands for the logistic model, such as Piegorsch and Casella (1988). However, the confidence bands given by Piegorsch and Casella are conservative under a single interval restriction, and it is shown in this article that their bands can be sharpened using the methods proposed here. Furthermore, no method has yet appeared in the literature for constructing one-sided confidence bands for the logistic model, and no work has been done for building confidence bands for the probit model, over a limited range of the predictor variable. This article provides methods for computing critical points in these areas.

Cite

@article{arxiv.1604.01242,
  title  = {Confidence Bands for the Logistic and Probit Regression Models Over Intervals},
  author = {Lucy Kerns},
  journal= {arXiv preprint arXiv:1604.01242},
  year   = {2016}
}

Comments

20 pages, 2 figures in 2015, Communication in Statistics - Theory and Methods

R2 v1 2026-06-22T13:25:30.971Z