Hostname: page-component-cd9895bd7-mkpzs Total loading time: 0 Render date: 2024-12-23T05:36:26.110Z Has data issue: false hasContentIssue false

A comparison theorem for conditioned Markov processes

Published online by Cambridge University Press:  14 July 2016

G. O. Roberts*
Affiliation:
University of Nottingham
*
Postal address: Department of Mathematics, University of Nottingham, University Park, Nottingham NG7 2RD, UK.

Abstract

Intuitively, the effect of conditioning a one-dimensional process to remain below a certain (possibly time-dependent) boundary is to ‘push' the process downwards. This paper investigates the effect of such conditioning, and finds the class of processes for which our intuition is accurate. It is found that ordinary stochastic inequalities are in general unsuitable for making statements about such conditioned processes, and that a stronger type of inequality is more appropriate.

The investigation is motivated by applications in estimation of boundary hitting time distributions.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 1991 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Ikeda, N. and Watanabe, S. (1981) Stochastic Differential Equations and Diffusion Processes. North-Holland, Amsterdam.Google Scholar
Lehmann, E. L. (1959) Testing Statistical Hypotheses. Wiley, New York.Google Scholar
Lerche, H. R. (1986) Boundary Crossing of Brownian Motion. Lecture Notes in Statistics 40, Springer-Verlag, Berlin.CrossRefGoogle Scholar
Pollak, M. and Siegmund, D. (1986) Convergence of quasi-stationary distribution for stochastically monotone Markov processes. J. Appl. Prob. 23, 215220.CrossRefGoogle Scholar
Roberts, G. O. (1987) Limit laws for conditioned diffusions with application to boundary hitting times. Warwick University Statistics Department, Research Report No 141.Google Scholar
Roberts, G. O. (1989) Asymptotic approximations for Brownian motion boundary hitting times. Ann. Prob. To appear.Google Scholar
Siegmund, D. (1986) Boundary crossing probabilities and statistical applications. Ann. Statist. 14, 361404.CrossRefGoogle Scholar
Wijsman, R. A. (1985) A useful inequality on ratio of integrals, with application to maximum likelihood estimation. J. Amer. Statist. Assoc. 80, 472475.CrossRefGoogle Scholar