Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 5154 for “"likelihood"”.
-
Maximum LQ-likelihood estimation.
Abstract not available.
-
Rethinking Maximum Likelihood Estimation
… models. I propose a novel alternative to Maximum Likelihood Estimation, most popular method for estimating parameters, and show how my proposed method mitigates bias, reduces overfitting and the overrepresentation of high frequency events, increases the representation of low frequency data, is …
-
Empirical Likelihood With Applications
Empirical likelihood, first introduced by Thomas and Grunkemeier (1975) and later extended in Owen (1988, 1990), is an effective and flexible nonparametric method based on a data-driven likelihood ratio function. It enjoys many advantages over other nonparametric methods, such as automatic …
-
Similarity-based likelihood judgment
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 1991.
-
Some aspects of empirical likelihood
… chapter 3, Asymptotic Optimality of Empirical Likelihood Tests With Weakly Dependent Data, we extend the result of Kitamura (2001) to stationary mixing data. The key thing inproving the large deviation optimality is that the empirical measure of the independently and identically distributed …
-
Asymptotic Likelihood Inference for Sharpe Ratio
… aimed at improving the accuracy of likelihood method have been proposed over the past three decades. Among them, Lugannani and Rice (1980) and Barndorff-Nielsen (1986) introduced two widely used tail area approximations with third order of convergence. Furthermore, Fraser(1988; …
-
Maximum likelihood estimation in dynamical systems
… only partially observed. <br>Here maximum likelihood methods are used for the estimation of the <br>parameters from noisy measurements and to construct the unobserved <br>components of a system. <br>These methods take into account the entire information about the <br>deterministic nature of …
-
Bayesian empirical likelihood for quantile regression
… regression is not equipped with a parametric likelihood, and therefore, Bayesian inference for quantile regression demands careful investigations. This thesis considers the Bayesian empirical likelihood approach to quantile regression. Taking the empirical likelihood into a Bayesian framework, …
-
RGB-D Likelihood for 3D Inverse Graphics
… data. We propose a novel 3D Neural Embedding Likelihood (3DNEL) over RGB-D images to address this gap. 3DNEL uses neural embeddings to predict 2D-3D correspondences from RGB and combines this with depth in a principled manner. 3DNEL is trained entirely from synthetic images and generalizes to …
-
Maximum likelihood Markov networks : an algorithmic approach
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2001.
-
The use of criminal background checks: does type of offense influence likelihood to interview, likelihood to hire, and salary?
To protect organizations from liabilities and litigation, background checks are becoming increasingly common during the hiring process. Correspondingly, many individuals have committed criminal offenses which often excludes them from being selected for a job. This study examines the effects of …
-
Maximum likelihood time-domain beamforming using simulated annealing
… coming from different directions, the maximum likelihood approach is used to estimate the source bearings and time series. Simulated annealing is used to implement the resulting time-domain beamformer. Broadband signals in spatially correlated noise are treated. Previous time-domain beamformers …
-
The algebraic statistics of sampling, likelihood, and regression
… but hard to analyze. We compute their maximum likelihood degree in dimension two and find it equal to $2n-3$ generically if the model has $n$ covariates. Discrete models with rational MLE are those discrete models for which likelihood estimation is easiest. We characterize them geometrically by …
-
Semi-Parametric Likelihood Functions for Bivariate Survival Data
… the two random variables and a nonparametric likelihood function for the unknown random variable. Associated properties are studied and investigated and applications with simulated and real data are given.</p>
-
Seer: Maximum likelihood regression for learning-speed curves
Restriction data tranferred 2014-07-01T11:24:02-05:00 Original Data Group with Access UIUC Users [automated] Release Date: none Reason: ETDs are only available to UIUC Users without author permission
-
Approximate likelihood for dependent networks and hyperlink predictions
… proposed method does not require specifying the likelihood function, which could be intractable for correlated binary connectivities. In addition, the proposed method allows for heterogeneity among edges among different communities. In theory, we show that incorporating correlation information …
-
A likelihood ratio analysis of digital phase modulation
Although the likelihood ratio forms the theoretical basis for maximum likelihood (ML) detection in coherent digital communication systems, it has not been applied directly to the problem of designing good trellis-coded modulation (TOM) schemes. The remarkably simple optimal receiver of minimum …
-
Statistical analysis of adaptive maximum-likelihood signal estimator
Thesis (Elec. E.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.
Page 1 of 258