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 219 for “"Maximum likelihood estimation"”.
-
Rethinking Maximum Likelihood Estimation
… the issue of bias in statistical parameter estimation, with a particular focus on deep generative 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 …
-
Maximum likelihood estimation in dynamical systems
… <br>are 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 …
-
Maximum likelihood estimation of spatially correlated soil properties
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Civil Engineering, 1985.
-
Exact Maximum Likelihood Estimation of the Kalman Filter Model
The interpretation of the Kalman filter model (KFM) used in this thesis is one where the transition equation allows the coefficients of a regression equation to follow an autoregressive-moving average process. Thus the KFM is a generalization of the random coefficients model.
-
Maximum likelihood estimation of a multivariate log-concave density
Density estimation is a fundamental statistical problem. Many methods are either sensitive to model misspecification (parametric models) or difficult to calibrate, especially for multivariate data (nonparametric smoothing methods). We propose an alternative approach using maximum likelihood under a …
-
Underwater Direction-of-Arrival Finding: Maximum Likelihood Estimation and Performance Analysis
… scenarios, and develop novel signal models, maximum likelihood: ML) estimation methods, and performance analysis results. We first examine the underwater scenarios where the noise on sensor arrays are spatially correlated, for which we consider using sparse sensor arrays consisting of widely …
-
Stochastic Volatility Models: Option Price Approximation, Asymptotics and Maximum Likelihood Estimation
… overcoming one of the key difficulties in the estimation problem. The method is applied to estimate three popular stochastic volatility models, two of which have not previously been amenable to maximum likelihood estimation with option price data other than through the use of proxies for the …
-
A generalized data regression system based on the maximum likelihood estimation
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 1980.
-
Maximum likelihood estimation of fractional Brownian motion and Markov noise parameters
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1992.
-
Penalized Joint Maximum Likelihood Estimation Applied to Two Parameter Logistic Item Response Models
… yield meaningless results. Recently, penalized estimation methods have been developed to analyze data sets that may include more variables than observations. The main focus of this study was to apply LASSO and ridge regression penalization techniques to IRT models in order to better estimate …
-
An Investigation of the Goodness of Fit of the Maximum Likelihood Estimation Procedure in Factor Analysis
Made available in DSpace on 2014-12-10T21:07:14Z (GMT). No. of bitstreams: 1 7207006.pdf: 9703683 bytes, checksum: 76d727416d3789faff802857c77e8979 (MD5) Previous issue date: 1971
-
Single View Coplanar Photogrammetry and Uncertainty Analysis for Traffic Accident Reconstruction
… and exterior orientation of the camera. Process maximum likelihood estimation (MLE) of the interior parameters of the camera or camera calibration and methods to provide uncertainty for those parameters are discussed. To find the maximum likelihood estimation of the exterior orientation of the …
-
Methods and Theory for Joint Estimation of Incidental and Structural Parameters in Latent Class Models
Marginal maximum likelihood estimation has become the standard for parameter estimation in latent variable models. However, there are instances when alternative estimators that jointly estimate incidental parameters and structural parameters might be easier to implement. A drawback to joint …
-
Mobile radiation sensor networks for source detection in a fluctuating background using geo-tagged count rate data
… a radiation sensor network is deployed, and a maximum likelihood estimation-based algorithm is developed to evaluate measurements from the sensor network and estimate the experimental area's radiation distribution and fluctuation. Using the reconstructed background radiation distribution and …
-
Frequency analysis of low flows: comparison of a physically based approach and hypothetical distribution methods
… a point mass probability for zero flows. Maximum likelihood estimation is used to estimate distribution parameters. Partial Duration Series is applied due to drawbacks of using only one low flow per year in annual minimum series. Two approaches were used in Partial Duration Series (i) …
-
Logspline Density Estimation with an Application to the Study of Survival Data of Lung Cancer Patients.
… sample data is studied. Our approach is to use maximum likelihood estimation to estimate the unknown density function from a space of linear splines that have a finite number of fixed uniform knots. In the end of this thesis, the method is applied to a real survival data set of lung cancer …
-
Impacts of great western development on agricultural production in the west of China
… approach with several economic theories such as maximum likelihood estimation (MLE), measurement of technical inefficiency and estimation of technical change in the production function. An important contribution of this thesis is empirical estimation of stochastic frontier production function for …
Page 1 of 11