JSTOR Daily

Nonparametric Maximum Likelihood Estimation of the Structural Mean of a Sample of Curves

A random sample of curves can be usually thought of as noisy realisations of a compound stochastic process X(t) = Z{W(t)}, where Z(t) produces random amplitude variation and W(t) produces random ...
JSTOR Daily

Maximum Likelihood Estimation from Linear Combinations of Discrete Probability Functions

In this article the problem of obtaining the maximum likelihood estimates of the parameters from a special type of linear combination of discrete probability functions is discussed. It is shown that ...
Risk

Maximum likelihood estimation error and operational value-at-risk stability

The challenge of using small sample sizes for operational risk capital models fitted via maximum likelihood estimation is well recognized, yet the literature generally provides warning examples rather ...
IEEE

Maximum Likelihood Estimation Based Complex-Valued Robust Chinese Remainder Theorem and Its Fast Algorithm

Abstract: In this paper, we investigate complex-valued Chinese remainder theorem (C-CRT) with erroneous remainders, where the moduli are Gaussian integers and the errors follow wrapped complex ...
Risk

Smoothing algorithms by constrained maximum likelihood: methodologies and implementations for Comprehensive Capital Analysis and Review stress testing and International ...

In the process of loan pricing, stress testing, capital allocation, modeling of probability of default (PD) term structure and International Financial Reporting Standard 9 expected credit loss ...
GitHub

Maximum Likelihood Reinforcement Learning

This is the official PyTorch implementation of our paper "Maximum Likelihood Reinforcement Learning" by Fahim Tajwar*, Guanning Zeng*, Yueer Zhou, Yuda Song, Daman Arora, Yiding Jiang, Jeff Schneider, ...