Preconditioning of Markov Chain Monte Carlo Simulations Using
... increase the acceptance rate of MCMC calculations. Here the acceptance rate refers to the ratio between the number of accepted permeability samples and the number of times of solving the fine-scale non-linear PDE system. The method consists of two-stages. At the first stage, using coarse-scale runs ...
... increase the acceptance rate of MCMC calculations. Here the acceptance rate refers to the ratio between the number of accepted permeability samples and the number of times of solving the fine-scale non-linear PDE system. The method consists of two-stages. At the first stage, using coarse-scale runs ...
The Median Value of Fuzzy Numbers and its Applications in
... Kumar [12]. However, some of these methods are computationally complex and difficult to implement, and others are counterintuitive and not discriminating. Furthermore, many of them produce different ranking outcomes for the same problem. In 1988, Lee and Li [13], proposed a comparison of fuzzy numbers ...
... Kumar [12]. However, some of these methods are computationally complex and difficult to implement, and others are counterintuitive and not discriminating. Furthermore, many of them produce different ranking outcomes for the same problem. In 1988, Lee and Li [13], proposed a comparison of fuzzy numbers ...
Simplifying Expressions Involving Radicals
... and Brent we describe approximation algorithms for algebraic numbers. To describe these approximation algorithms via elementary operations on integers is at least inaccurate and confusing. Although as far a asymptotic run times are concerned and one is very careful it would not cause too much troubl ...
... and Brent we describe approximation algorithms for algebraic numbers. To describe these approximation algorithms via elementary operations on integers is at least inaccurate and confusing. Although as far a asymptotic run times are concerned and one is very careful it would not cause too much troubl ...
ch07_new
... What elements does the data array contain after the following statements? double[] data = new double[10]; for (int i = 0; i < data.length; i++) ...
... What elements does the data array contain after the following statements? double[] data = new double[10]; for (int i = 0; i < data.length; i++) ...
Multi-Digit Whole Number and Decimal Fraction Operations • Grade 5
... In Topic B, place value understanding moves toward understanding the distributive property via area diagrams which are used to generate and record the partial products (5.OA.1, 5.OA.2) of the standard algorithm (5.NBT.5). Topic C moves students from whole numbers to multiplication with decimals, aga ...
... In Topic B, place value understanding moves toward understanding the distributive property via area diagrams which are used to generate and record the partial products (5.OA.1, 5.OA.2) of the standard algorithm (5.NBT.5). Topic C moves students from whole numbers to multiplication with decimals, aga ...
Factorization of multivariate polynomials
... Definition 2.3. Let R be a UFD and f = ni=0 ai xi ∈ R[x]. The content cont(f ) of f is defined as gcd(a0 , . . . , an ). If cont(f ) = 1, f is called primitive. The primitive part pp(f ) of f is defined as f /cont(f ). Definition 2.4. Let R[x] be a unique factorization domain. Any non-constant polyn ...
... Definition 2.3. Let R be a UFD and f = ni=0 ai xi ∈ R[x]. The content cont(f ) of f is defined as gcd(a0 , . . . , an ). If cont(f ) = 1, f is called primitive. The primitive part pp(f ) of f is defined as f /cont(f ). Definition 2.4. Let R[x] be a unique factorization domain. Any non-constant polyn ...
mixture densities, maximum likelihood, EM algorithm
... populations in the mixture.) A variety of cases of this problem and several approaches to its solution have been the subject of or at least touched on by a large, diverse set of papers spanning nearly ninety years. We begin by offering in the next section a cohesive but very sketchy review of those ...
... populations in the mixture.) A variety of cases of this problem and several approaches to its solution have been the subject of or at least touched on by a large, diverse set of papers spanning nearly ninety years. We begin by offering in the next section a cohesive but very sketchy review of those ...
LEC01 - aiub study guide
... Write a pseudocode algorithm to find the two smallest numbers in a sequence of numbers (given as an array). ...
... Write a pseudocode algorithm to find the two smallest numbers in a sequence of numbers (given as an array). ...
pdf file
... There is nothing special about these particular numbers. They work for any choices of d, m, n, x and y. Now let’s try using this to see why 15 cannot divide 230. We divide 30 into 230. It goes in 7 times with remainder 20. By Theorem ??, this means ...
... There is nothing special about these particular numbers. They work for any choices of d, m, n, x and y. Now let’s try using this to see why 15 cannot divide 230. We divide 30 into 230. It goes in 7 times with remainder 20. By Theorem ??, this means ...
Probability Distribution Function of the Internal Rate of Return in One
... return for certain one and two period stochastic engineering economy problems. In each type of the problem, the roots of the internal rate of return are derived initially. The probability distribution of the internal rate of return is then found for different combinations of random cash flows. These ...
... return for certain one and two period stochastic engineering economy problems. In each type of the problem, the roots of the internal rate of return are derived initially. The probability distribution of the internal rate of return is then found for different combinations of random cash flows. These ...
Fisher–Yates shuffle
The Fisher–Yates shuffle (named after Ronald Fisher and Frank Yates), also known as the Knuth shuffle (after Donald Knuth), is an algorithm for generating a random permutation of a finite set—in plain terms, for randomly shuffling the set. A variant of the Fisher–Yates shuffle, known as Sattolo's algorithm, may be used to generate random cyclic permutations of length n instead. The Fisher–Yates shuffle is unbiased, so that every permutation is equally likely. The modern version of the algorithm is also rather efficient, requiring only time proportional to the number of items being shuffled and no additional storage space.Fisher–Yates shuffling is similar to randomly picking numbered tickets (combinatorics: distinguishable objects) out of a hat without replacement until there are none left.