Finding Gaussian Curvature of Lifespan  Distribution

William W. S. Chen

doi:10.4236/am.2014.521316

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Applied Mathematics > Vol.5 No.21, December 2014

Finding Gaussian Curvature of Lifespan Distribution ()

William W. S. Chen

Department of Statistics, The George Washington University, Washington DC, USA.

DOI: 10.4236/am.2014.521316 PDF HTML XML 3,645 Downloads 4,195 Views Citations

Abstract

The objective of this paper is to review the lifespan model. This paper will also suggest four additional general alternative computational methods not mentioned in Kass, R.E. and Vos, P.W. [1] [2]. It is not intended to compare the four formulas to be used in computing the Gaussian curvature. Four different formulas adopted from Struik, D.J. [3] are used and labeled here as (A), (B), (C), and (D). It has been found that all four of these formulas can compute the Gaussian curvature effectively and successfully. To avoid repetition, we only presented results from formulas (B) and (D). One can more easily check other results from formulas (A) and (C).

Keywords

Christoffel Symbols, Gamma, Gaussian Curvature, Inverse Gaussian, Metric Tensor, Mixed Riemann Curvature Tensor, Weibull

Share and Cite:

Chen, W. (2014) Finding Gaussian Curvature of Lifespan Distribution. Applied Mathematics, 5, 3392-3400. doi: 10.4236/am.2014.521316.

Conflicts of Interest

The authors declare no conflicts of interest.

References

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