JSTOR Daily

Maximum likelihood estimation using composite likelihoods for closed exponential families

In certain multivariate problems the full probability density has an awkward normalizing constant, but the conditional and/or marginal distributions may be much more tractable. In this paper we ...
JSTOR Daily

On Sequential Maximum Likelihood Estimation for Exponential Families of Stochastic Processes

A particular type of one-parameter exponential family of stochastic processes is studied. Many widely used models for stochastic processes are of this type. In particular, sampling rules for which the ...
IEEE

Fast Maximum Likelihood Estimation Of Big Data Spatial Autoregressive Model: Matrix Exponential Spatial Specification Approach

Abstract: In big data, Spatial Autoregressive models experience several difficulties in parameter estimation, such as non-linear optimization, theoretical complexity, and computation. One way to ...
IEEE

DOA Parameter Estimation with 1-bit Quantization Bounds, Methods and the Exponential Replacement

Abstract: While 1-bit analog-to-digital conversion (ADC) allows to significantly reduce the analog complexity of wireless receive systems, using the exact likelihood function of the hardlimiting ...
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 ...