Parameter specification for simulated data sets
Use of simulated data sets to evaluate the fidelity of Metagenomic processing methods
... metagenomic data has already being generated 12 methods to process these data are in their infancy, and objective measures of their efficacy are ...of simulated metagenomic data sets of ...
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Visualization techniques for heterogeneous and multidimensional simulated building performance data sets
... However, at the same time, the assessment of thousands of variants increases the complexity of data interpretation. A study based on 28 interviews of building performance optimization experts (Attia et al. 2013) ...
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Using Simulated Annealing to Study Behaviour of Various Exam Timetabling Data Sets
... same data set is at least as stable as the ...the data set ...particular data set is similar in behaviour to others when using one function, but very different when using a different ...this ...
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Using Simulated Pseudo Data To Speed Up Statistical Predictive Modeling From Massive Data Sets
... some data sets, ...training data, which contains these conditionally correlated features displays properties that cannot be obtained from the simulated pseudo data of the generative ...
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PERFORMANCE SPECIFICATION TEST PROGRAM SETS
... UUT Data Sheet, when selected, shall be displayed. This data shall include but not be limited to the ID part number and nomenclature, cable part numbers and quantities, accessories required, and any ...
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Evaluation of association tests for rare variants using simulated data sets in the Genetic Analysis Workshop 17 data
... It is natural to ask why the average powers of these four methods are low for the analysis of the GAW17 data sets. There are three possible reasons. First, the phenotypes Q1 and Q2 do not completely depend ...
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Evaluating two methods of estimating error variances using simulated data sets with known errors
... correlation parameter a increases from 0, the differences between the estimated and true error variances ...three data sets, estimates of error standard deviations using a large sample of real ...
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Proficiency Testing of Virus Diagnostics Based on Bioinformatics Analysis of Simulated In Silico High Throughput Sequencing Data Sets
... sequence data analysis are highly affected by bioinformatics pro- cessing using publicly available and custom tools and databases and thus differ widely between individuals and ...tificial, simulated in ...
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Proficiency testing of virus diagnostics based on bioinformatics analysis of simulated in silico high-throughput sequencing data sets
... sequence data analysis are highly affected by bioinformatics pro- cessing using publicly available and custom tools and databases and thus differ widely between individuals and ...tificial, simulated in ...
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Proficiency Testing of Virus Diagnostics Based on Bioinformatics Analysis of Simulated In Silico High-Throughput Sequencing Data Sets
... sequence data analysis are highly affected by bioinformatics pro- cessing using publicly available and custom tools and databases and thus differ widely between individuals and ...tificial, simulated in ...
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Compositionality and Compatibility of Parameterization and Parameter Passing in Specification Languages
... formal parameter specification and the specification denoted by the body of the ...parameterized data types are assumed to denote a class of functors from the category of models of the formal ...
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Poisson models for simulated data
... Overdispersion is often encountered when fitting very simple parametric models, such as those based on the Poisson distribution. The Poisson distribution has one free parameter and does not allow for the variance ...
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Improved performance of crystal structure solution from powder diffraction data through parameter tuning of a simulated annealing algorithm
... The six best performing SA parameter configurations (CR/ N 1 /N 2 = 0.27/73/56, 0.27/73/61, 0.27/73/51, 0.27/60/63, 0.25/35/ 86 and 0.25/46/62) from these tests were then tested against all molecules in the ...
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Specification tests for time-varying parameter models with stochastic volatility
... Recall that a positive log Bayes factor represents evidence in support of the unrestricted model against the restricted version—i.e., the model with some form of stochastic volatil- ity is preferred. Table 2 shows that ...
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Bootstrap Specification Tests with Dependent Observations and Parameter Estimation Error
... of parameter estimation error does not enter the limiting distribution of the test statistic; and Inoue (1999) who studies di®erent conditional features, such as conditional symmetry and conditional ...of ...
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Limit sets and switching strategies in parameter-optimal iterative learning control
... The paper then considers the fundamental question of whether or not the ILC algorithm can be modified to eliminate the problems and ensure that convergence to a non-zero element of the limit set is replaced by a ...
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Faster Fixed Parameter Tractable Algorithms for Finding Feedback Vertex Sets
... F OMIN , F. V., AND T HILIKOS , D. M. 2003. Dominating sets in planar graphs: branch-width and exponential speed-up. In Proceedings of the 14th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA). ACM, New ...
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Utilities for Partitioned Data Sets
... unit parameter specifies a type of input/output ...your data, and how it can most efficiently be stored and accessed. Parameter values can be requirements of the program you are ...
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Julia sets in parameter spaces
... A
knowledgements. We are very grateful to Bodil Branner, Adrien Douady, John Hubbard and Carsten Petersen for en
ouraging us. We would like to thank the department of mathemati
s of the University at Cornell for its ...
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PARAMETER-LESS SIMULATED KALMAN FILTER
... Simulated Kalman Filter (SKF) was first introduced in by Ibrahim et al. (2015) as an optimizer for unimodal optimization problems. The benchmarking of the SKF algorithm later has been extended to simple ...
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