共查询到20条相似文献,搜索用时 9 毫秒
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David J. Scott Diethelm W��rtz Christine Dong Thanh Tam Tran 《Computational Statistics》2011,26(3):459-476
In this paper we demonstrate a recursive method for obtaining the moments of the generalized hyperbolic distribution. The
method is readily programmable for numerical evaluation of moments. For low order moments we also give an alternative derivation
of the moments of the generalized hyperbolic distribution. The expressions given for these moments may be used to obtain moments
for special cases such as the hyperbolic and normal inverse Gaussian distributions. Moments for limiting cases such as the
skew hyperbolic t and variance gamma distributions can be found using the same approach. 相似文献
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Björn Holmquist 《随机分析与应用》2013,31(3):273-278
Expressions in vector notation are given for the central moments, the non–central moments and the cumulants of arbitrary order of the multivariate normal distribution 相似文献
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In this work, we give the expectation and the covariance formulas for the support weight distributions of linear codes. 相似文献
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Let ?(n,x) be the local time of a random walk on Z2. We prove a strong law of large numbers for the quantity Ln(α)=∑x∈Z2?(n,x)α for all α≥0. We use this result to describe the distribution of the local time of a typical point in the range of the random walk. 相似文献
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Greg Littmann 《Acta Analytica》2012,27(1):29-44
There is a strong intuition that for a change to occur, there must be a moment at which the change is taking place. It will
be demonstrated that there are no such moments of change, since no state the changing thing could be in at any moment would
suffice to make that moment a moment of change. A moment in which the changing thing is simply in the state changed from or the state changed to cannot be the moment of change, since these states are respectively before and after the change; moreover, to select one
of these moments over the other as the moment of change would be arbitrary. A moment in which the changing thing is neither
in the state changed from nor in the state changed to cannot be the moment of change, since there are changes for which it
is impossible for something to be in neither state. Finally, the moment of change cannot be a moment in which the changing
thing is in both the state changed from and the state changed to, as suggested by Graham Priest and others. Even if, like
proponents of this view, we are willing to accept the contradictions that the account entails, it is demonstrated that on
such a model, every change would require an infinite number of other changes, every change would take an infinite amount of
time, and some changes would occur without occurring at any time. Further, the model is grossly counterintuitive, with the
exact nature of the counterintuitive element depending on what model of time and space one endorses. Finally, it is demonstrated
that this model is incompatible with the Leibniz Continuity Condition. 相似文献
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Conrey J. B.; Farmer D. W.; Keating J. P.; Rubinstein M. O.; Snaith N. C. 《Proceedings London Mathematical Society》2005,91(1):33-104
We give a new heuristic for all of the main terms in the integralmoments of various families of primitive L-functions. The resultsagree with previous conjectures for the leading order terms.Our conjectures also have an almost identical form to exactexpressions for the corresponding moments of the characteristicpolynomials of either unitary, orthogonal, or symplectic matrices,where the moments are defined by the appropriate group averages.This lends support to the idea that arithmetical L-functionshave a spectral interpretation, and that their value distributionscan be modelled using Random Matrix Theory. Numerical examplesshow good agreement with our conjectures. 2000 Mathematics SubjectClassification 11M26, 15A52. 相似文献
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《Journal of Mathematical Analysis and Applications》1987,127(1):237-245
This paper is motivated by [2], where we have given necessary and sufficient conditions for a given basis P in the space of polynomials to be orthogonal with respect to the measure ϱdφ for a certain function ϱ ϵ L2(dφ). Let P = {pi: i = 0, 1, …}, p0 = 1. Then the conditions are (1) a multivariate analog of the three-term recurrence relation holds, see Section 4 for details; and (2) {qi = ∑j = 0∞ cij Pj, i = 0, 1, …} is a φ-orthonormal basis in the space of polynomials for some coefficients cij such that ∑i = 0∞ ci02 <-∞. This paper provides an algebraic condition (a condition on the coefficients ci0) such that ϱ satisfies ∥p∥ <B, Bϵ (0, ∞], and has a cone-positivity property. In particular, our results imply that ϱ is nonnegative a.e. if ∑i = 0∞ ci02 < ∞ and ∑jϵ Sk cj0 qj defines nonnegative polynomials for certain finite sets S1, S2, … of integers. 相似文献
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Sadanori Konishi Takakazu Sugiyama 《Annals of the Institute of Statistical Mathematics》1981,33(1):27-33
Summary Normalizing transformations of the largest and the smallest latent roots of a sample covariance matrix in a normal sample
are obtained, when the corresponding population roots are simple. Using our results, confidence intervals for population roots
may easily be constructed. Some numerical comparisons of the resulting approximations are made in a bivariate case, based
on exact values of the probability integral of latent roots. 相似文献
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The generalized method of moments (GMM) is a very popular estimation and inference procedure based on moment conditions. When likelihood-based methods are difficult to implement, one can often derive various moment conditions and construct the GMM objective function. However, minimization of the objective function in the GMM may be challenging, especially over a large parameter space. Due to the special structure of the GMM, we propose a new sampling-based algorithm, the stochastic GMM sampler, which replaces the multivariate minimization problem by a series of conditional sampling procedures. We develop the theoretical properties of the proposed iterative Monte Carlo method, and demonstrate its superior performance over other GMM estimation procedures in simulation studies. As an illustration, we apply the stochastic GMM sampler to a Medfly life longevity study. Supplemental materials for the article are available online. 相似文献
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We find moments of a process of Markov random evolutions in a finite-dimensional space. 相似文献
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Moments of generalized Wishart distributions are obtained through tensor differential forms and reindexing. 相似文献