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Browse All Reviews > Mathematics Of Computing (G) > Probability And Statistics (G.3) > Multivariate Statistics (G.3...)
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1-9 of 9
Reviews about "Multivariate Statistics (G.3...)":
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Efficient computations of multivariate normal distributions with applications to finance
Lai Y. Modelling and simulation (Proceedings of the 17th IASTED International Conference on Modelling and Simulation, Montreal, Canada, May 24-26, 2006) 522-527, 2006. Type: Proceedings
Lai presents a significant simulation of multivariate normal distribution. All of the bivariate distributions can be converted into one-dimensional integrals, and most cases of the trivariate normal distributions can be converted into ...
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Dec 6 2006 |
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Comparison with a standard via fully sequential procedures
Kim S. ACM Transactions on Modeling and Computer Simulation 15(2): 155-174, 2005. Type: Article
The focus of this very well-written paper is the determination of a system whose expected performance measures are larger or smaller than a single system, with the goal of subsequently presenting the smallest and largest system....
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Jun 7 2005 |
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Independent component analysis: a tutorial introduction
Stone J., MIT Press, Cambridge, MA, 2004. Type: Book (9780262693158)
The independent component analysis (ICA) method is introduced in this excellent book, through examples from signal processing. It is addressed to beginners, as well as professionals, engineers, and scientists....
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Mar 23 2005 |
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Finite-order weights imply tractability of linear multivariate problems
Wasilkowski G., Woźniakowski H. Journal of Approximation Theory 130(1): 57-77, 2004. Type: Article
Specificity, validity, and reliability, not to mention time and money, all underscore the importance of multivariate statistics. This area of statistics is of vital importance to business, government, and social science....
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Jan 26 2005 |
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On improved projection techniques to support visual exploration of multidimensional data sets
Tejada E., Minghim R., Nonato L. Information Visualization 2(4): 218-231, 2003. Type: Article
One of the problems in visualizing multi-dimensional data is that the n-dimensions must be projected onto a two-dimensional display, often losing important information in the process. In addition, if an analyst inten...
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Jun 9 2004 |
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Approximations to the distribution of the sample correlation matrix
Kollo T., Ruul K. Journal of Multivariate Analysis 85(2): 318-334, 2003. Type: Article
The derivation of multivariate density expansions for a sample correlation matrix R is dealt with in this paper. An introduction discusses the sample correlation matrix; the treatment is standard. This is followed by...
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Aug 20 2003 |
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Asymptotic theory for multivariate GARCH processes
Comte F., Lieberman O. Journal of Multivariate Analysis 84(1): 61-84, 2003. Type: Article
Strong consistency and asymptotic normality of the quasi-maximum likelihood estimator for multivariate generalized autoregressive conditional heteroskedasticity (GARCH) is proven in this paper. The asymptotic normality is proven under ...
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Jul 31 2003 |
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 Influence diagnostics for generalized linear mixed models: applications to clustered data
Xiang L., Tse S., Lee A. Computational Statistics & Data Analysis 40(4): 759-774, 2002. Type: Article
The generalized linear mixed model (GLMM) is one of many extensions of the usual linear model. In a GLMM, observations are not necessarily independent, but it is assumed that data can be clustered so that observations in different clus...
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Apr 17 2003 |
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An algorithm and fortran program for multivariate LAD (l1 of l2) regression
Kaufman E., Taylor G., Mielke P., Berry K. Computing 68(3): 275-287, 2002. Type: Article
The authors consider the problem of fitting a linear combination of functions to observed data in a multivariate model. They discuss combinations of approximations in the l1 and l2 norm. A Fortran program that ca...
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Jan 21 2003 |
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