According to the basic theory of Bayes, research into Bayes estimation of multigroup ranging measurement test and derive formulas used in range and density test when average value and variance are unknow.
For landslide with a few test values,the shear strength parameters can be optimized by Bayes estimation; and for neogenic landslide without test values,the shear strength parameters of slide zone clay can be obtained with some data of neighbouring and similar landslides by Bayes estimation.
Abstract In this paper, when prior distribution of the failure rate is in form of Gamma distribution Gamma(1,b), hierachical Bayesian estimation of the failure rate in exponential distribution has been come out from zero failure data.
When for life distribution such as logarithm-normal distribution of certain hydraulic pump, Bayesian estimation of failure probability is given, and after introducing failure information, Bayesian estimation and synthesized estimation of failure probability are given. Synthesized estimation of reliability for certain hydraulic pump under zero-failure data condition is also obtained.
A process method for zero-failure data of the product is developed synthesized new Bayesian estimate method. When the case of zero-failure data, put forward the definition of new Bayesian estimate for failure rate, and given the new Bayesian estimate of failure rate.
In this paper, the Bayesian method, an estimate method for parameter in reliability engineering is put forward. The author gives definition of the new Bayesian estimate for failure probability and failure rate, and shows the estimate of the failure probability and the failure rate by new Bayesian method.
Bayesian method is applied to derive the failure probability under DOOR The method takes beta distribution as the prior distribution. The scale parameter of beta distribution is not fixed, but follows a uniform distribution. Adopting the weighted least square estimate method, the formulas of reliability distribution parameter is obtained.
A family of distributions is defined for which the generalized Bayesian estimate of a real parameter θ, constructed according to the repeated choice, does not depend on the choice of the even convex loss function from a sufficiently wide class.
When samples of products are tested and no failur events occur, the definition of expected Bayesian estimate is introduced and the estimates of failure probability and failure rate are provided.
It is shown that the LS estimate of the LICA problem is identical to the Bayesian estimate based on the mode of the posterior distribution.
When the decoding algorithm used for this calculation approximated an optimal, Bayesian estimate of the relative likelihoods, the percentage correct increased from 14% correct (chance was 5% correct) with one neuron to 67% with 14 neurons.
For eliciting a prior distribution which can be used in deriving a Bayesian estimate, a computerized-simulation method is introduced.
Bayes prediction density and regression estimation - A semiparametric approach
Bayes prediction limits and predictive estimators under absolute-error loss can readily be computed using iterative methods.
Bayes Prediction Robustness in Terms of L1-Distortions of Prior Probability Distribution
It is important to notice that this second seed is correctly predicted compared to the Bayes'prediction with PBs, which gives the PB series mnopa.
Retrospective estimates of the strength and form power of Bayes prediction of amino acid sites under positive selection.
Abstract This paper discusses the multivariate linear model Where ε is distributed as a specialclass of matrix-elliptical distribution,It's characteristic matrix being We obtain Bayes estiumation β.of parameteie mateix β,under condition of known;V>0 known,0 unknown,Known V>0 unknown.respetively.
Abstract In this paper, when prior distribution of the failure rate is in form of Gamma distribution Gamma(1,b), hierachical Bayesian estimation of the failure rate in exponential distribution has been come out from zero failure data. Then the reliability estimation of zero failure data are come out, finally calculation is performed regarding to practical problem.