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On px1 dependent random variables having each (p-1)x1 sub-vector made up of IID observations with examples

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  • Mukhopadhyay, Nitis

Abstract

It is not easy to locate a non-Np joint probability density function (p.d.f.) such that each (p-1)-dimensional sub-vector would consist of p-1 independent and identically distributed (i.i.d.) standard normal variables, but the construction of such a multivariate distribution can be interesting. We address this problem and provide examples of this and other kinds including joint p.d.f.s where each (p-1)-dimensional sub-vector consists of p-1 i.i.d. normal, Laplace or lognormal variables.

Suggested Citation

  • Mukhopadhyay, Nitis, 2009. "On px1 dependent random variables having each (p-1)x1 sub-vector made up of IID observations with examples," Statistics & Probability Letters, Elsevier, vol. 79(14), pages 1585-1589, July.
    • Handle: RePEc:eee:stapro:v:79:y:2009:i:14:p:1585-1589
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    1. de Paula, Aureo, 2008. "Conditional Moments and Independence," The American Statistician, American Statistical Association, vol. 62, pages 219-221, August.
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    Cited by:

    1. Mukhopadhyay, Nitis, 2010. "A convolution identity and more with illustrations," Statistics & Probability Letters, Elsevier, vol. 80(23-24), pages 1980-1984, December.

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