Risk

Estimating operational risk capital: the challenges of truncation, the hazards of maximum likelihood estimation, and the promise of robust statistics

In operational risk measurement, the estimation of severity distribution parameters is the main driver of capital estimates, yet this remains a nontrivial challenge for many reasons. Maximum ...
JSTOR Daily

Maximum Likelihood Estimation for Two-Parameter Decreasing Hazard Rate Distributions Using Censored Data

Problems of maximum likelihood estimation are discussed for shape and scale parameters from certain decreasing hazard rate distributions, typically either mixed-exponential or "work-hardened." ...
Simon Fraser University

Parameter Estimation

Maximum likelihood estimation of the parameters of a statistical model involves maximizing the likelihood or, equivalently, the log likelihood with respect to the parameters. The parameter values at ...
Risk

Operational risk models and asymptotic normality of maximum likelihood estimation

Operational risk models commonly employ maximum likelihood estimation (MLE) to fit loss data to heavy-tailed distributions. Yet several desirable properties of MLE (eg, asymptotic normality) are ...
JSTOR Daily

Bayesian Semiparametric Estimation of Discrete Duration Models: An Application of the Dirichlet Process Prior

This paper proposes a Bayesian estimator for a discrete time duration model which incorporates a non-parametric specification of the unobserved heterogeneity distribution, through the use of a ...