Bayes comprehensive assessment of reliability for binomial products by using test information of similar product

For reliability assessment of binomial products, the history sample and the current sample often follow different populations, which have remarkable effect on reliability assessment. The similarity degree between the history sample and the current sample were studied by similar system analysis, and their similarity degree was denoted by inheritance factor. Then, the history posterior was obtained from the history sample and the innovation posterior was given by the non-informative prior, which reflect the history information of similar products and the current test information respectively; the complex posterior was obtained from the history posterior and the innovation posterior via inheritance factor, and statistical inference was made on the basis of the complex posterior. This method makes full use of information of similar products and emphasizes the particular characteristic of the evaluated product.