Many products always operate under various complex environment conditions. To describe the dynamic influence of environment factors on their reliability, a method of reliability sensitivity analysis is proposed. In th...Many products always operate under various complex environment conditions. To describe the dynamic influence of environment factors on their reliability, a method of reliability sensitivity analysis is proposed. In this method, the location parameter is assumed as a function of relevant environment variables while the scale parameter is assumed as an unknown positive constant. Then, the location parameter function is constructed by using the method of radial basis function. Using the varied environment test data, the log-likelihood function is transformed to a generalized linear expression by describing the indicator as Poisson variable. With the generalized linear model, the maximum likelihood estimations of the model coefficients are obtained. With the reliability model, the reliability sensitivity is obtained. An instance analysis shows that the method is feasible to analyze the dynamic variety characters of reliability along with environment factors and is straightforward for engineering application.展开更多
In this paper,a statistical prediction problem under ordered location and scale parameters are considered.Double-shrinkage predictors are given which use all the available data and improve on single-shrinkage predicto...In this paper,a statistical prediction problem under ordered location and scale parameters are considered.Double-shrinkage predictors are given which use all the available data and improve on single-shrinkage predictors,and hence the best equivariant predictors.展开更多
文摘Many products always operate under various complex environment conditions. To describe the dynamic influence of environment factors on their reliability, a method of reliability sensitivity analysis is proposed. In this method, the location parameter is assumed as a function of relevant environment variables while the scale parameter is assumed as an unknown positive constant. Then, the location parameter function is constructed by using the method of radial basis function. Using the varied environment test data, the log-likelihood function is transformed to a generalized linear expression by describing the indicator as Poisson variable. With the generalized linear model, the maximum likelihood estimations of the model coefficients are obtained. With the reliability model, the reliability sensitivity is obtained. An instance analysis shows that the method is feasible to analyze the dynamic variety characters of reliability along with environment factors and is straightforward for engineering application.
文摘In this paper,a statistical prediction problem under ordered location and scale parameters are considered.Double-shrinkage predictors are given which use all the available data and improve on single-shrinkage predictors,and hence the best equivariant predictors.
