No CrossRef data available.
Article contents
An extension theorem for convex functions and an application to Teicher's characterization of the normal distribution
Part of:
Real functions
Published online by Cambridge University Press: 26 February 2010
Extract
The main aim of this note is the proof of the following
Let −∞ ≤ a > b ≤ ∞ and let A ⊂ (a, b) be a measurable set such that λ((a, b)\A) = 0, where λ denotes Lebesgue measure on ℝ. Let f: A→ℝ be a measurable and midconvex function, i.e.
whenever. Then there exists a convex functionsuch that.
MSC classification
Secondary:
26A51: Convexity, generalizations
- Type
- Research Article
- Information
- Copyright
- Copyright © University College London 1987
References
1.Findeisen, P.. Die Charakterisierung der Normalverteilung nach GauB. Metrika, 29 (1982), 55–64.CrossRefGoogle Scholar
3.Roberts, A. W. and Varberg, D. E.. Convex Functions (Acad. Press, New York and London, 1973).Google Scholar
4.Teicher, H.. Maximum likelihood characterization of distributions. Ann. Math. Statist., 32 (1961), 1214–1222.CrossRefGoogle Scholar