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Showing 1 to 20 of 26 for “"Fisher information matrix"”.
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Security of Watermarking Schemes Against Sensitivity Analysis Attacks
… watermark 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 …
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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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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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Confidence Ellipses Under the Inverse Gaussian Distribution
… maximum 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 …
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Statistical Analysis of Longitudinal and Multivariate Discrete Data
… Finding 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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Modeling and estimation in Gaussian graphical models : maximum-entropy methods and walk-sum analysis
… algorithm 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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Likelihood Theory and Methods for Generalized Linear Mixed Models
… available for the asymptotic variance-covariance matrix for such estimators contain limits and expectations over the response distribution, hence such results are not in ready-to-use forms when carrying out tasks such as constructing studentized confidence intervals or optimal design …
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Properties of Weighted Generalized Beta Distribution of the Second Kind
… reverse hazard function, moments are presented. Fisher information matrix (FIM) and estimates of model parameters under censoring including progressive Type II for the Dagum distribution are presented. WGB2 proved to be in the generalized beta-F family of distributions, and maximum likelihood …
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Management and Analysis of Localization Information in Uncrewed Aerial Systems
… improves the timeliness of localization-information exchange, enabling tighter formation keeping, faster synchronization, and overall behavior more consistent with the low-latency, high-reliability goals of URLLC-class services. Finally, we develop a localization-driven trajectory …
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A Finite Mixture Approach to Covariance Structure Modeling With Unknown, Heterogeneous Populations
… derived through the calculation of the observed Fisher information matrix of the FMCS model. The model was evaluated by assessing the accuracy of recovering known mixture and covariance structure parameters in synthetic (e.g., Monte Carlo) data as well as by judging the increase in …
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Design and Analysis of Toxicological Experiments with Multiple Endpoints and Synergistic and Inhibitory Effects
… these probabilities is to segregate necessary information from un-necessary information through inducing them as weights in to the Fisher Information Matrix. Illustrative examples from simulated data were provided to illustrate all methods and criteria.</p>
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Bayesian model averaging on hydraulic conductivity estimation and groundwater head prediction
… The second problem is with using the Kashyap information criterion (KIC) in the approximation of posterior model probabilities, which tends to prefer highly uncertain model by considering the Fisher information matrix. The Bayesian information criterion (BIC) is recommended because it is able …
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Some sequential estimation problems in logistic regression models
… a MLE of $\beta\sb0$ and $\Sigma\sp{-1}$ is the Fisher information matrix. If $\Sigma$ is known then $R\sb d=\{Z\in{\bf R}\sp p:n(Z-\\beta\sb n)\sp T\Sigma(Z-\\beta\sb n)$ $\le n\lambda d\sp2\}$ defines a confidence ellipsoid for $\beta\sb0$, with maximum axis $\le 2d$ and $P(\beta\sb0\in R\sb …
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Parameter and topology uncertainty for optimal experimental design
… parameter uncertainty as estimated by the Fisher information matrix. We found, using a computational scenario where the true parameters were unknown, that the parameters of the model could be recovered from noisy data in a small number of experiments if the experiments were chosen well. We …
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Damage Detection and Sensor Placement Strategies for Structures Under Frequency-Domain Dynamics
… a key challenge is the gathering of sufficient information through sensors such that modern damage estimation mechanisms can identify and diagnose anomalies with certainty. </p><p>To that end, we formulate a simultaneous inversion and optimal experimental design (OED) framework for models …
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Generalized gamma spatial ARMA conditional model for speckled data: theoretical developments and applications
… nature of SAR data. We derive the score vector, Fisher information matrix, and sth moments and estimate the two-dimensional generalized gamma ARMA (2D-GGARMA) model parameters through an iterative process. Furthermore, we explicitly establish the relationship between our model and the SAR image …
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Fisher Information in X-ray/Gamma-ray Imaging Instrumentation Design
… random effects. Recovering maximum possible information about event attributes of interest requires a systematic collection of calibration data and analysis provided by estimation theory. In this context, a likelihood model provides a description of the connection between the observed signals …
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Analysis of Discrete Choice Probit Models with Structured Correlation Matrices
… parameters and analytical expressions for the Fisher information matrix to compute their standard errors. Using simulations, we compare the performance of probit models with logit models in both large sample case as well as small samples. We conclude that the probit models are more …
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Distributed Estimation and Performance Limits in Resource-constrained Wireless Sensor Networks
… transmit with such that the determinant of the Fisher information matrix (FIM) at any given time step is maximized. The performance of the proposed compressive sensing based sensor management methodology in terms of accuracy of inference is investigated.</p> <p>For the Bayesian parameter …
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