The Experts below are selected from a list of 243 Experts worldwide ranked by ideXlab platform
Bengt Muthen - One of the best experts on this subject based on the ideXlab platform.
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moments of the censored and truncated Bivariate Normal Distribution
British Journal of Mathematical and Statistical Psychology, 1990Co-Authors: Bengt MuthenAbstract:Published results on the moments of censored and truncated Bivariate Normal Distributions do not include explicit formulas for all combinations of limits in a form that is readily adapted for computation. Moments for truncation and censoring that can take place both from above and below in both variables are given in a general form from which special cases are easily obtained. The attenuation of the correlation coefficients is studied in a series of graphs and related to examples of factor analysis.
Shiny Mathew - One of the best experts on this subject based on the ideXlab platform.
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inference on p x y p x y for Bivariate Normal Distribution based on ranked set sample
METRON, 2019Co-Authors: Manoj Chacko, Shiny MathewAbstract:In this paper, we consider the problem of estimation of $$R=P(X
Manoj Chacko - One of the best experts on this subject based on the ideXlab platform.
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inference on p x y p x y for Bivariate Normal Distribution based on ranked set sample
METRON, 2019Co-Authors: Manoj Chacko, Shiny MathewAbstract:In this paper, we consider the problem of estimation of $$R=P(X
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estimation of parameters of Bivariate Normal Distribution using concomitants of record values
Statistical Papers, 2007Co-Authors: Manoj Chacko, Yageen P ThomasAbstract:In this paper, we discuss the concomitants of record values arising from the well-known Bivariate Normal Distribution BVND(µ1, µ2,σ1,σ2, ρ). We have obtained the best linear unbiased estimators of µ2 and σ2 when ρ is known and derived some unbiased linear estimators of ρ when µ2 and σ2 are known, based on the concomitants of first n record values. The variances of these estimators have been obtained.
Fan Hongyi - One of the best experts on this subject based on the ideXlab platform.
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generalized wigner operator and Bivariate Normal Distribution in p q phase space
Communications in Theoretical Physics, 2008Co-Authors: Fan Hongyi, Wang TongtongAbstract:We introduce a kind of generalized Wigner operator, whose Normally ordered form can lead to the Bivariate Normal Distribution in p-q phase space. While this Bivariate Normal Distribution corresponds to the pure vacuum state in the generalized Wigner function phase space, it corresponds to a mixed state in the usual Wigner function phase space.
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Normally ordered Bivariate Normal Distribution forms of two mode mixed states with entanglement involved
Chinese Physics Letters, 2008Co-Authors: Fan Hongyi, Wang Tongtong, Hu LiyunAbstract:Based on the technique of integration within an ordered product of operators we have demonstrated that single-mode mixed states' density matrices can be recast into the Normally ordered Gaussian forms [Chin. Phys. Lett. 24 (2007) 3322]. Here we employ the Weyl ordering invariance under similar transformations to show that some two-mode mixed states with entanglement involved can be put into Normally ordered form in the Bivariate Normal Distribution too and its marginal Distributions can be analysed. In this way, density operators of quantum statistics can be analogous to mathematical statistics, and calculation of variances can be simplified.
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coordinate momentum intermediate representation and marginal Distributions of quantum mechanical Bivariate Normal Distribution
Communications in Theoretical Physics, 2008Co-Authors: Fan Hongyi, Lou SenyueAbstract:We introduce Bivariate Normal Distribution operator for state vector |ψ〉 and find that its marginal Distribution leads to one-dimensional Normal Distribution corresponding to the measurement probability |λ,ν〈x|ψ〉|2, where |x〉λ,ν is the coordinate-momentum intermediate representation. As a by-product, the one-dimensional Normal Distribution in statistics can be explained as a Radon transform of two-dimensional Gaussian function.
William Q Meeker - One of the best experts on this subject based on the ideXlab platform.
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the nontruncated marginal of a truncated Bivariate Normal Distribution
Psychometrika, 1993Co-Authors: Barry C Arnold, Robert J Beaver, Richard A Groeneveld, William Q MeekerAbstract:Inference is considered for the marginal Distribution ofX, when (X, Y) has a truncated Bivariate Normal Distribution. TheY variable is truncated, but only theX values are observed. The relationship of this Distribution to Azzalini's “skew-Normal” Distribution is obtained. Method of moments and maximum likelihood estimation are compared for the three-parameter Azzalini Distribution. Samples that are uniformative about the skewness of this Distribution may occur, even for largen. Profile likelihood methods are employed to describe the uncertainty involved in parameter estimation. A sample of 87 Otis test scores is shown to be well-described by this model.