Quality based costing and Monte Carlo
Identification of Water Quality Model Parameter Based on Finite Difference and Monte Carlo
... water quality model parameter directly affect the accuracy of water quality numerical simula- ...Chain Monte Carlo is developed to identify the parame- ters of water quality model in ...
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Monte Carlo-Based Tail Exponent Estimator
... α (based on the whole data set) and the estimated tail exponent. The tail exponent is estimated only on an arbitrarily chosen part of the data (Hill, 1975; Weron, 2001). Since extreme observations of prices on ...
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Four essays on sequential Monte Carlo and quasi-Monte Carlo methods
... approach based on a tempered sequential Monte Carlo (SMC) ...Using Monte Carlo simulations, we provide strong evidence regarding the stat- istical performances of the SMC sampler as ...
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Monte Carlo methods
... In practice, either a reasonable choice for q is available, or not. The first case occurs when, e.g., π is almost unimodal and concentrates its mass on a small region of X . A Gaussian centered at this small region with ...
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Fast Monte Carlo Simulations for Quality Assurance in Radiation Therapy
... fast Monte Carlo dose calculation packages suitable for different application ...famous Monte Carlo code PENELOPE and build a new code system gPENELOPE that runs 5 times faster and remains the ...
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Updating the TSP Quality Plan Using Monte Carlo Simulation
... The consistent failure of large-scale devel- opment programs not only costs a lot of time and money, it delays the introduction of promising new technology and deprives our fighting forces of the tools they need to ...
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Monte Carlo inference and maximization for phrase based translation
... 3.4 Discussion These results show very little difference between the decoding methods, indicating that the Gibbs sam- pling decoder can perform as well as a standard DP based max-derivation decoder with these ...
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M3C: Monte Carlo reference-based consensus clustering.
... ECC employs an entropy-based utility function to fuse many basic partitions into a single consensus structure. A future challenge is to systematically evaluate the performance of a wider range of consensus ...
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A Monte Carlo based analysis of optimal design criteria
... are based on only a single realization and the limiting ...not based on a single realization of the observation process, but uses a large number of realizations, with, of course, increased computational ...
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Optimal Mortgage Refinancing Based on Monte Carlo Simulation
... Refinancing Based on Monte Carlo Simulation Jin Zheng, Siwei Gan, Xiaoxia Feng, and Dejun Xie Abstract—The pricing of mortgages in the context of stochas- tic interest rate plays an important role ...
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Orthogonal Array Sampling for Monte Carlo Based Rendering
... that Monte Carlo integration will eventually converge to the correct answer, it is useful to know how quickly it will ...makes Monte Carlo integration so appealing for many use cases is that ...
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Monte Carlo evaluation of resampling-based hypothesis tests
... . Monte Carlo estimation of the power function at a particular alternative would proceed simply by generating many independent data sets and computing the proportion of ...this Monte Carlo ...
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Monte Carlo-based statistical methods (MASM11/FMS091)
... Weight degeneration is a universal problem with the SIS method and is due to the fact that the particle weights are generated through subsequent multiplications. This drawback prevented[r] ...
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The Monte Carlo Based Uncertainty Health Risk Assessment Associated with Rural Drinking Water Quality
... present, Monte Carlo Simulation is often used to deal with those uncertainly issues, it apply the method of probabilistic statistics to indicate the un- certainty of parameters, thus, it can present better ...
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Activity-Based Costing and Quality Management
... China produces 80% of the world’s baseballs, every single baseball pitched in the major leagues is made in a Costa Rican factory owned by RAWLINGS SPORT- ING GOODS COMPANY . A Rawlings baseball begins life as a “pill,” ...
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Energy Study of Monte Carlo and Quasi-Monte Carlo Algorithms for Solving Integral Equations
... The MC and QMC algorithms are perceived as computationally intensive, but naturally par- allel. The so-called “master-worker” model is usable for dynamic load-balancing, while static load-balancing is sufficient in the ...
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The jackknife in Monte Carlo studies
... reporting Monte Carlo ...the Monte Carlo descriptive ratio statistics discussed in Section ...3, based on individual estimators and their jackknife variance estimate in each sample, is ...
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CONTROLLED SEQUENTIAL MONTE CARLO
... 1) based on a current sequence of proposal distributions, running a SMC method to obtain a collection of samples that approximate the sequence of SMC target distributions; 2) using these samples as support points, ...
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Project Report of Monte Carlo
... of quality, especially in relation to price, and (2) their attention to garment care instructions, which affects their satisfaction with product ...of quality and price of slacks and various other branded ...
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Sequential Monte Carlo with transformations
... and raising Eq. (17) χ t ( g ) to the power 4. These latter two approaches use a lineage proposal where the probability is more concentrated on a smaller number of lineages. Figure 3 shows majority-rule consensus trees ...
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