Monotonicity of the (reversed) hazard rate of the (maximum) minimum in bivariate distributions

被引:0
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作者
Ramesh C. Gupta
Rameshwar D. Gupta
Pushpa L. Gupta
机构
[1] University of Maine,Department of Mathematics and Statistics
[2] University of New Brunswick,Department of Computer Science and Applied Statistics
来源
Metrika | 2006年 / 63卷
关键词
Bivariate distributions; Farlie-Gumbel-Morgenstern distributions; Monotonicity of the hazard rate; Sarmanov family;
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摘要
It is well known that in the case of independent random variables, the (reversed) hazard rate of the (maximum) minimum of two random variables is the sum of the individual (reversed) hazard rates and hence the onotonicity of the (reversed) hazard rate of the marginals is preserved by the monotonicity of the (reversed) hazard rate of the (maximum) minimum. However, for the bivariate distributions this property is not always preserved. In this paper, we study the monotonicity of the (reversed) hazard rate of the (maximum) minimum for two well known families of bivariate distributions viz the Farlie-Gumbel-Morgenstern (FGM) and Sarmanov family. In case of the FGM family, we obtain the (reversed) hazard rate of the (maximum) minimum and provide several examples in some of which the (reversed) hazard rate is monotonic and in others it is non-monotonic. In the case of Sarmanov family the (reversed) hazard rate of the (maximum) minimum may not be expressed in a compact form in general. We consider some examples to illustrate the procedure
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页码:223 / 241
页数:18
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