Results 221 to 230 of about 38,563 (254)

The inverse Gaussian process with a skew-normal distribution as a degradation model

Communications in Statistics - Simulation and Computation, 2019
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 app...
Xudan Chen, Xinli Sun, Xiong Ding, Jue Tang   +3 more
openaire   +1 more source

Remaining Useful Life Prediction for Heterogeneous Wearing Cutting Tools Based on Inverse Gaussian Process and Bayesian Inference

2023 5th International Conference on System Reliability and Safety Engineering (SRSE), 2023
The wear of cutting tools can lead to tool failures, and thus accurate remaining useful life (RUL) prediction for tools is important. Meanwhile, the wear process of tools from a same population usually present heterogeneous patterns.
Yu Luo, Biao Lu
semanticscholar   +1 more source

WARPED GAUSSIAN PROCESSES FOR PROGNOSTIC HEALTH MONITORING

Proceedings of the 13th International Workshop on Structural Health Monitoring, 2022
Gaussian process regression is a powerful method for predicting states associated with uncertainty. A common application field is to predict damage states of structural systems.
Simon Pfingstl, Christian Braun, M. Zimmermann   +2 more
semanticscholar   +1 more source

Reliability analysis of inverse Gaussian processes with two-stage degenerate paths

Heliyon
For randomly degraded products undergoing a two-stage degradation process, traditional random effects models assume that the degradation rate follows a symmetrically normal distribution. However, certain products exhibit asymmetric degradation rates.
Yu-ying Liang, Zaizai Yan, Lijun Sun
semanticscholar   +1 more source

Numerical analysis on quadratic hedging strategies for normal inverse Gaussian models

, 2018
The authors aim to develop numerical schemes of the two representative quadratic hedging strategies: locally risk minimizing and mean-variance hedging strategies, for models whose asset price process is given by the exponential of a normal inverse ...
Takuji Arai, Yuto Imai, Ryo Nakashima
semanticscholar   +1 more source

Acceleration invariance principle for Hougaard processes in degradation analysis

Naval Research Logistics, 2023
Accelerated degradation tests (ADTs) are widely used to assess lifetime information under normal use conditions for highly reliable products. For the accelerated tests, two basic assumptions are that changing stress levels does not affect the underlying ...
Chien‐Yu Peng, Yi-Shian Dong, Tsai‐Hung Fan   +2 more
semanticscholar   +1 more source

Approximation for the Normal Inverse Gaussian Process Using Random Sums

Stochastic Analysis and Applications, 2009
We approximate the normal inverse Gaussian (NIG) process with random summations. The random sum we introduce is a random walk subordinated to the first passage time of another independent random walk; the model is interpreted as an internal mechanism at small scale that generates the NIG process.
openaire   +1 more source

Applications of Gaussian-Inverse Wishart Process Regression Models in Claims Reserving

Variance
Gaussian processes are stochastic processes based on the normal distribution (i.e., collections of normal random variables indexed by a mathematical set).
Marco De Virgilis, G. Carnevale
semanticscholar   +1 more source

Application of Normal Inverse Gaussian Process in European Option Pricing

Journal of Statistics and Economics
The traditional Black-Scholes (BS) model, based on the geometric Brownian motion assumption, struggles to account for the fat-tail, spike, and volatility time-varying characteristics of asset prices in financial markets, leading to pricing deviations in options.
openaire   +1 more source

Pricing of First Touch Digitals under Normal Inverse Gaussian Processes

, 2006
O. Kudryavtsev, S. Levendorskiĭ
semanticscholar   +1 more source