Likelihood Ratio Sensitivity Analysis for Markovian Models of Highly Dependable Systems

1990 ◽  
Author(s):  
Marvin K. Nakayama ◽  
Ambuj Goyal ◽  
Peter W. Glynn
Keyword(s):  
Sensitivity Analysis ◽  
Likelihood Ratio ◽  
Dependable Systems ◽  
Markovian Models

Likelihood Ratio Sensitivity Analysis for Markovian Models of Highly Dependable Systems

1994 ◽  
Vol 42 (1) ◽  
pp. 137-157 ◽  
Author(s):  
Marvin K. Nakayama ◽  
Ambuj Goyal ◽  
Peter W. Glynn
Keyword(s):  
Sensitivity Analysis ◽  
Likelihood Ratio ◽  
Dependable Systems ◽  
Markovian Models

A unified framework for simulating Markovian models of highly dependable systems

1992 ◽  
Vol 41 (1) ◽  
pp. 36-51 ◽  
Author(s):  
A. Goyal ◽  
P. Shahabuddin ◽  
P. Heidelberger ◽  
V.F. Nicola ◽  
P.W. Glynn
Keyword(s):  
Unified Framework ◽  
Dependable Systems ◽  
Markovian Models

scholarly journals Statistical Surveillance of Structural Breaks in Credit Rating Dynamics

Entropy ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. 1072
Author(s):  
Haipeng Xing ◽  
Ke Wang ◽  
Zhi Li ◽  
Ying Chen
Keyword(s):  
Likelihood Ratio ◽  
Global Economy ◽  
Structural Breaks ◽  
Credit Rating ◽  
Credit Market ◽  
Statistical Process ◽  
Transition Dynamics ◽  
Markovian Models ◽  
Ratio Rule ◽  
Detection Rule

The 2007–2008 financial crisis had severe consequences on the global economy and an intriguing question related to the crisis is whether structural breaks in the credit market can be detected. To address this issue, we chose firms’ credit rating transition dynamics as a proxy of the credit market and discuss how statistical process control tools can be used to surveil structural breaks in firms’ rating transition dynamics. After reviewing some commonly used Markovian models for firms’ rating transition dynamics, we present several surveillance rules for detecting changes in generators of firms’ rating migration matrices, including the likelihood ratio rule, the generalized likelihood ratio rule, the extended Shiryaev’s detection rule, and a Bayesian detection rule for piecewise homogeneous Markovian models. The effectiveness of these rules was analyzed on the basis of Monte Carlo simulations. We also provide a real example that used the surveillance rules to analyze and detect structural breaks in the monthly credit rating migration of U.S. firms from January 1986 to February 2017.

A likelihood ratio test for detecting patterns of disease-marker association

1997 ◽  
Vol 61 (4) ◽  
pp. 335-350 ◽  
Author(s):  
A. P. MORRIS ◽  
J. C. WHITTAKER ◽  
R. N. CURNOW
Keyword(s):  
Likelihood Ratio ◽  
Likelihood Ratio Test ◽  
Ratio Test ◽  
Disease Marker
Sign in / Sign up

Export Citation Format

Share Document