Simon Fraser University

MLE for User-Defined Likelihood Functions

There are three SAS procedures that enable you to do maximum likelihood estimation of parameters in an arbitrary model with a likelihood function that you define: PROC MODEL, PROC NLP, and PROC IML.
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

Example 5.6: Maximum Likelihood Weibull Estimation

The following data are taken from Lawless (1982, p.193) and represent the number of days it took rats painted with a carcinogen to develop carcinoma. The last 2 observations are censored data from a ...
JSTOR Daily

A modern maximum-likelihood theory for high-dimensional logistic regression

This is a preview. Log in through your library . Abstract Students in statistics or data science usually learn early on that when the sample size n is large relative to the number of variables p, ...