Stress-strength reliability for general bivariate distributions
详细信息    查看全文
文摘
An expression for the stress-strength reliability mmlsi9" class="mathmlsrc">mathImg" data-mathURL="/science?_ob=MathURL&_method=retrieve&_eid=1-s2.0-S1110256X16000213&_mathId=si9.gif&_user=111111111&_pii=S1110256X16000213&_rdoc=1&_issn=1110256X&md5=32f87e1ad8999599a8d0bb31b602cfde">mg class="imgLazyJSB inlineImage" height="16" width="131" alt="View the MathML source" title="View the MathML source" src="/sd/grey_pxl.gif" data-inlimgeid="1-s2.0-S1110256X16000213-si9.gif">mathContainer hidden">mathCode"><math altimg="si9.gif" overflow="scroll"><mrow><mi>Rmi><mo>=mo><mi>Pmi><mo>(mo><mrow><msub><mi>Xmi><mn>1mn>msub><mo><mo><mspace width="0.16em">mspace><msub><mi>Xmi><mn>2mn>msub>mrow><mo>)mo>mrow>math> is obtained when the vector (m>Xm><sub>1sub>, m>Xm><sub>2sub>) follows a general bivariate distribution. Such distribution includes bivariate compound Weibull, bivariate compound Gompertz, bivariate compound Pareto, among others. In the parametric case, the maximum likelihood estimates of the parameters and reliability function m>Rm> are obtained. In the non-parametric case, point and interval estimates of m>Rm> are developed using Govindarajulu's asymptotic distribution-free method when m>Xm><sub>1sub> and m>Xm><sub>2sub> are dependent. An example is given when the population distribution is bivariate compound Weibull. Simulation is performed, based on different sample sizes to study the performance of estimates.
NGLC 2004-2010.National Geological Library of China All Rights Reserved.
Add:29 Xueyuan Rd,Haidian District,Beijing,PRC. Mail Add: 8324 mailbox 100083
For exchange or info please contact us via email.