Inverse Gaussian Process regression for likelihood-free inferenceHongqiao WangJinglai LiTengchao YuZiqiao Ao
Inverse Gaussian processRandom effectsThis paper conducts a Bayesian analysis for bivariate degradation models based on the inverse Gaussian (IG) process. Assume that a product has two quality characteristics (QCs) and each of the QCs is governed by an IG process. The dependence of the QCs is ...
This article incorporates a skew-normal distribution into an inverse Gaussian (IG) process to represent the unit-to-unit variability of the degradation rate, while a symmetrical distribution or approximately symmetrical distribution is commonly adopted in the IG process. Then we derive the corresponding...
This study proposes a degradation model based on an inverse normal-gamma mixture of an inverse Gaussian process. This article presents the properties of the lifetime distribution and parameter estimation using the EM-type algorithm, in addition to providing a simple model-checking procedure to assess...
SPRT and CUSUM results for the inverse gaussian process mean when the value of the shape parameter of the density is known are presented in this paper.doi:10.1080/03610929608831869Rick L. Edgeman, Professor & DirectorMarcel Dekker, Inc.Communications in Statistics...
In this article, an inverse Gaussian process (IGP)-based prediction approach for solving DMOPs is proposed. Unlike most traditional approaches, this approach exploits the IGP to construct a predictor that maps the historical optimal solutions from the objective space to the decision space. A ...
2.6 The normal inverse gaussian process Barndorff and Nielsen (1998) proposed the normal inverse Gaussian (NIG) distribution as a possible model for the stock price. This process may also be represented as a time-changed Brownian motion, where the time change T(t) is the first passage time ...
Finally, the accuracy and effectiveness of the proposed model are demonstrated through two case studies. The results show that the improved IG process model can improve the RUL prediction accuracy. 展开 关键词: Hydraulic piston pump Inverse Gaussian process Prognostics Degradation modeling Remaining ...
We present an inverse kinematics solver based on Gaussian process latent variable models (GP-LVM). Because of the high-dimension of motion capture data, Analyzing them directly is a very hard work. We map the motion capture data from higher-dimensional observation space to two-dimensional latent...
Inverse Gaussian processstep-stress accelerated degradation testproportional degradation rate modeloptimal test planasymptotic variancetraversal search algorithmThe purpose of this paper is to address the optimal design of the step-stress accelerated degradation test (SSADT) issue when the degradation process...