Global ETD Search
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Showing 1 to 20 of 51 for “"Information matrix"”.
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Security of Watermarking Schemes Against Sensitivity Analysis Attacks
… estimation problem. The inverse of the Fisher information matrix provides an algorithm-independent bound on the covariance matrix of the estimation error. A general strategy for the attacker is to select the distribution of auxiliary test signals that minimizes the trace of the inverse Fisher …
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Ill-conditioned information matrices and the generalized linear model: an asymptotically biased estimation approach
… scoring. This iterative procedure involves a key matrix, the information matrix. Ill-conditioning of the information matrix can be responsible for making many desirable properties of the parameter estimates unattainable. Some asymptotically biased alternatives to maximum likelihood estimation are …
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Optimum experimental designs for models with a skewed error distribution: with an application to stochastic frontier models
… an organisation. Three methods for approximating information matrices are presented. An approximation is required since the information matrix contains complicated expressions, which are difficult to evaluate. However, only one method, 'Method 1', is recommended because it guarantees nonnegative …
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Hypothesis testing when a nuisance parameter is identified only under the alternative hypothesis
… cannot be applied due to the singularity of the information matrix. Probably best known examples are the problems of unknown change points and the mixtures of distributions in econometrics and statistics. Davies (1977, 1987) proposes a general solution to this type of problems.
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Parameter sensitivity, estimation and convergence: an information approach
… noise. The convergence analysis uses the eigen-information of the correlation matrix (really its inverse, the Fisher information matrix) for a chosen parameterization. This analysis explains why various state-space structures have different convergence properties, 1.e., why for the same system …
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Statistical Properties of Kumaraswamy Generalized Inverse Weibull Distribution
… kurtosis, _entropy, generalized entropy, Fisher information matrix, informational energy are studied. Estimates of the model parameters via several methods including maximum likelihood (MLE), and method of moments (MME) are presented.</p>
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Specification tests for autoregressive conditional heteroskedastic models with applications to exchange rates of Asian countries
The White information matrix (IM) test is applied to the linear regression model with autoregressive conditional heteroskedastic (ARCH) errors. ARCH models are used widely in analyzing economic and financial time series data. However, in practice, the models are not often thoroughly tested. We …
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Sparse Bayesian information filters for localization and mapping
… posterior in the canonical form, in terms of the information (inverse covariance) matrix. When sparse, this representation is amenable to computationally efficient Bayesian SLAM filtering. However, while a large majority of the elements within the normalized information matrix are very small in …
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Weighted Optimality of Block Designs
… idea that optimality functions of the treatment information matrix are invariant to treatment permutation. This implies equal interest in all treatments. In practice, however, there are many experiments where not all treatments are equally important. When selecting a design for such an …
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Specification tests and a reformulation of frontier models: An alternative approach to efficiency estimation
… tests for these models. The tests are based on information matrix and moment tests principles.
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Modeling Conditional Heteroskedasticity in Time Series and Spatial Analysis
… test for spatial autoregressive model using the information matrix (IM) test principle. As a byproduct of my test development, I obtain a general model that has similar features like autoregressive conditional heteroskedasticity (ARCH) in time series context. My suggested spatial ARCH (SARCH) …
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An Item Response Unfolding Model for Graphic Rating Scales
… of the estimates are computed from the observed information matrix. Simulation studies were conducted to investigate the behavior of the estimators in two simple versions of the model, one with only location parameters and the other with a common dispersion parameter. Survey data from the …
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Large-area visually augmented navigation for autonomous underwater vehicles
… (AUVs) while exploiting the inertial sensor information that is routinely available on such platforms. We adopt a systems-level approach exploiting the complementary aspects of inertial sensing and visual perception from a calibrated pose-instrumented platform. This systems-level strategy …
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Optimal Blocking for Three Treatments and BIBD Robustness - Two Problems in Design Optimality
… design parameters, or special structure in the information matrix). The other is construction of designs satisfying those conditions. Most papers deal with either optimality conditions, or design construction in accordance with desired combinatorial properties, but not both. This dissertation …
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Sparse Bayesian information filters for localization and mapping
… posterior in the canonical form, in terms of the information (inverse covariance) matrix. When sparse, this representation is amenable to computationally efficient Bayesian SLAM filtering. However, while a large majority of the elements within the normalized information matrix are very small in …
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Confidence Ellipses Under the Inverse Gaussian Distribution
… likelihood equations and estimating the Fisher Information matrix for the construction of a normal approximation which gives ellip- tical con dence regions by approximating the Inverse Gaussian Distribution. The second part which is the computational centres on constructing asymptotic con dence …
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Statistical Analysis of Longitudinal and Multivariate Discrete Data
… the maximum likelihood estimates and the Fisher information matrix for these models requires computation of multivariate normal probabilities. We also discuss several efficient algorithms for calculating multivariate normal integrals. For the multivariate probit and multivariate Poisson …
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The automatic design of experiments : Some practical algorithms.
… design by using the trace and determinant of the information matrix. The application of the algorithms is illustrated with examples drawn from the physical sciences, particularly metallurgy. The algorithms developed in the study have been fully implemented using standard Fortran 4 with a few …
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Modeling and estimation in Gaussian graphical models : maximum-entropy methods and walk-sum analysis
… is that we exploit sparsity of the Fisher information matrix in models defined on chordal graphs. The merits of this approach are investigated by recovering the graphical structure of some simple graphical models from sample data. Next, we present a general class of algorithms for …
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Trajectory optimization for target localization using small unmanned aerial vehicles
… sensors. Combining UAV state estimates with information gathered by the imaging sensors leads to bearing measurements of the target that can be used to determine the target's location. This 3-D bearings-only estimation problem is nonlinear and traditional filtering methods produce biased and …
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