The Sequential Sampling Paradigm applied to Valuation
Bootstrap methods applied to spatial variogram estimation and sequential sampling
... Data were generated by sampling the process Z(-) on the integer grid starting from time point 1. We considered various combinations of parameter values under both models [r] ...
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Improving valuation sampling of EQ-5D health states
... a valuation survey which related only to theoretical response patterns which are never seen in real life because of such ...was applied involved excluding states which exhibited one of three prohibited ...
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Browne et al., 2012] is a modern heuristic search paradigm that has been applied to a large number of sequential decision making problems
... We sample 10 neural net models at epochs 10,20,. . .,100. Each neural net model is then combined with MoHex’s MCTS and played against MoHex-CNN with the same 1000 simulations per move. Following a practice in the litera- ...
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Optimal Sequential Sampling Plans Using Dynamic Programming Approach
... Sequential sampling plans are designed to enhance the performance of sampling ...sample. Sequential sampling plans are often applied where minimizing sample size is very ...
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Global Sampling for Sequential Filtering over Discrete State Space
... and applied the GS and the SISR algorithm for online ...unbiased sampling strate- gies are used: multinomial sampling and the modified strat- ified sampling (detailed in the ...mial ...
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Negative Examples for Sequential Importance Sampling of. Binary Contingency Tables
... importance sampling is a widely-used approach for randomly sampling from complex ...been applied in a variety of fields, such as protein folding [6], population genetics [3], and signal processing ...
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Negative Examples for Sequential Importance Sampling of Binary Contingency Tables
... importance sampling is a widely-used approach for estimating the cardi- nality of a large set of combinatorial ...been applied in a variety of fields, such as protein folding [14], population genetics [9], ...
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Modeling inconsistencies in people's preferential choices with sequential sampling models
... In an applied setting, researchers might also be interested in the subjective importance weights that people assign to specific attributes. For instance, in a consumer context marketing companies want to infer the ...
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Sequential Multi Task Spectral Clustering Scheme with Active Learning paradigm
... and applied to various ...study Sequential clustering is going to perform with the priority based correlation ...This sequential prediction finds the important labels between the multi ...
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Probabilistic Asset Valuation Applied to Natural Resource Projects
... In conjunction with the 1-point analysis, firms often use DCF simple scenarios and simulation as a form of sensitivity analysis. Simple scenarios include testing different variable assumptions individually to determine ...
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An investigation of sequential sampling method for crossdocking simulation output variance reduction
... 2. BACKGROUND For the design and analysis of complex models, where the performance of such models is measured using confidence interval half width on mean values, it is sometimes difficult to achieve a target precision ...
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Empirical Bayes Prediction for Variables Process Mean in Sequential Sampling Plan
... studied Bayesian approach in sequential sampling plan by variables assuming normally distributed data with unknown mean but known variance. The Bayesian approach is applied in parameters estimation. ...
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Decision Making Using Sequential Equation Modelling Applied for Pellet Production
... a sampling strategy, was taken into account that the sample covers approximately equal number of men and women in the mentioned towns, with different education and different occupations, and that includes ...
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Sequential Poisson Sampling
... Poisson sampling with PRN is used for this purpose in New Zealand, see Templeton ...random sampling without replacement) was suggested by Atmer, Thulin, and BaÈcklund (1975) and is now used for most ...
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Hierarchical Knowledge Gradient for Sequential Sampling
... a sequential sampling policy for noisy discrete global optimization and ranking and selection, in which we aim to efficiently explore a finite set of alternatives before selecting an alternative as best ...
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Systems of Sequential Grammars Applied to Parsing
... Chapter 6 Conclusion This work was focused on systems of sequential grammars and their adaptation for parsing. In another words, the aim was to create and later implement an effective parser based on these ...
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The cloud paradigm applied to e-Health
... We would like to highlight that for small numbers of servers, the relation between the waiting time of both queues does not change, keeping it at constant levels. On the other hand, for large computing systems, with huge ...
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Incorporating Model Uncertainty into the Sequential Importance Sampling Framework using a Model Averaging Approach, or Trans Dimensional Sequential Importance Sampling
... The definition of the transition probability above will affect the validity of the method and also its efficiency. One should remember that although particles are not independent of their parallels, with which they share ...
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Applied Sampling and Reconstruction of Signals on the Sphere
... proposed sampling scheme and SHT allows for accurate reconstruction of the HRTF over the whole sphere, including unmeasured locations, provided that a suitable band-limit is ...
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Sampling Methods Applied to Fisheries Science
... In order to achieve these objectives, landing statistics (total annual catch) are needed. In this case it is assumed that all the fish caught in one year, in the area and by all fleet components come from a single ...
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