Sampling of the parameter space
Populations of Models, Experimental Designs and Coverage of Parameter Space by Latin Hypercube and Orthogonal Sampling
... of parameter sets for the initial population, sampled from a possibly high-dimensional parameter ...the parameter space, depending on costing constraints and therefore limits of ...A ...
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MOMCMC: An efficient Monte Carlo method for multi-objective sampling over real parameter space
... real parameter space. In Section 4.1, the MOMCMC sampling results on a simple multi-objective problem with three objective functions are compared with those generated by multi-objective optimization ...
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Iterative importance sampling algorithms for parameter estimation
... in parameter space, which suggests that posterior variances are reduced significantly compared to the broad ...the parameter regimes that are consistent with the data we ...
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Visualization of parameter space for image analysis
... of Parameter Space for Image Analysis ...optimize parameter set- ...conventional parameter optimization process for image analysis and formulate user ...on parameter sampling and ...
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Improve the Active Subspace Method by Partitioning the Parameter Space
... input space considering the corresponding uncertainty, and the model out- puts of the drawn inputs are collected as a data set for further ...than sampling from the full model, many choose to sample from ...
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Transitional annealed adaptive slice sampling for Gaussian process hyper-parameter estimation
... Slice Sampling with some recently developed Sequential Monte Carlo ...the sampling through delayed-rejection, the inclusion of an annealing scheme akin to Asymptotically Independent Markov Sampling ...
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Multiphase MCMC sampling for parameter inference in nonlinear ordinary differential equations
... surrogate space, fix the noise variance pa- rameter and sample the ODE parameters for N precorr steps, initiated at some estimate obtained during the smoothing ...
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A New Parameter of Statistic Equality of Sampling Lengths in Surface Roughness Measurement
... Additional momentum in the research activities related to filtration in surface metrology has been provided by the International Standardization Organization (ISO) which, according to [1], issued a document (а ...
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Space Efficiencies in Discourse Modeling via Conditional Random Sampling
... Random Sampling (CRS) Li and Church (2007) proposed CRS to approximate the contingency table between elements in a query, to be used in distributional similarity measures such as cosine similarity, correlation, ...
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Bayesian Space-Time Partitioning by Sampling and Pruning Spanning Trees
... the parameter estimates (either the normal mean or the Poisson rate) depends on the number of clusters we assume to implement the method as well as on the type of ...
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On the Consistency of Bootstrap Testing for a Parameter on the Boundary of the Parameter Space
... a parameter space (as often de…ned by inequality, or mixed equality/inequality, constraints) under the null ...for parameter constancy in random coe¢ cient models (Andrews, 2001; Carrasco and ...
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Visual Tracking by Sampling in Part Space
... part space, which contains sufficient regions to cover most structures of objects, and two online learned probabilities on it - the proposal distribution α and the acceptance ratio ...
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Investigating the parameter space of evolutionary algorithms
... the parameter-seeking ...that parameter space, in fact, tends to be rife with viable parameters, at least for the problems studied ...search space, defining the fitness function, designing ...
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A Comparison of Sampling Strategies for Parameter Estimation of a Robot Simulator
... The individual is selected for evaluation in reality that has the highest fitness in the latest tuned simulator (or, in the first iteration, a simulator with randomly chosen parameters). A[r] ...
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A canonical space-time state space model: state and parameter estimation
... were would be constructed via the algorithm given in Table I as III. E STIMATION The EM algorithm provides a well-known framework for ap- proaching the joint state and parameter estimation problem for the general, ...
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Improved Sampling of Decision Space for Pareto Estimation
... In this test, we employ the the ratio of two IGD values, DR P¯E , PˆE , defined as the ratio of the distance from P¯E to the actual PF over that from the PˆE to the actual PF, where P¯E [r] ...
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Trajectory similarity analysis in movement parameter space
... The aim of this paper is to propose a spatio-temporal similarity analysis method with the perspective of detecting trajectories with similar dynamic behaviour. That is, the method assesses the similarity of the evolution ...
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Nearest Neighbor Imputation for General Parameter Estimation in Survey Sampling
... Nearest neighbor imputation is popular for handling item nonresponse in survey sampling. In nearest neighbor imputation, the vector of the auxiliary variables is directly used in determining the nearest neighbor. ...
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Statistics and Probability Quarter 3 Module 4: Random Sampling,Parameter and Statistic, and Sampling Distribution of Statistics
... Random Sampling What’s In If a researcher wants to observe, examine or test a theory or hypothesis, he will consider the problem by selecting a section of the population of the study using a method called random ...
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Enhancement of K-Parameter Using Hybrid Stratified Sampling and Genetic Algorithm
... stratified sampling is also used in this research, where the sampling functions by dividing the population into homogeneous areas using stratification ...
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