Pages that link to "Item:Q4474669"

The following pages link to A kernel-distance-based multivariate control chart using support vector methods (Q4474669):

Displaying 27 items.

• General support vector representation machine for one-class classification of non-stationary classes (Q936411) (← links)
• Support vector regression based residual MCUSUM control chart for autocorrelated process (Q945289) (← links)
• A distance-based control chart for monitoring multivariate processes using support vector machines (Q1639226) (← links)
• Process monitoring using a generalized probabilistic linear latent variable model (Q1716441) (← links)
• Statistical Perspectives on “Big Data” (Q2787301) (← links)
• Probability Density Estimation via an Infinite Gaussian Mixture Model: Application to Statistical Process Monitoring (Q3435369) (← links)
• Robust kernel distance multivariate control chart using support vector principles (Q3532782) (← links)
• Generalized Control Charts for Non-Normal Data Using<i>g</i>-and-<i>k</i>Distributions (Q3543732) (← links)
• Integration of support vector machines and control charts for multivariate process monitoring (Q4914964) (← links)
• Robust Hotelling's T²control charts under non-normality: the case of<i>t</i>-Student distribution (Q4925428) (← links)
• High-dimensional data monitoring using support machines (Q5082664) (← links)
• Kernel methods for changes detection in covariance matrices (Q5084948) (← links)
• Principal component analysis-based control charts using support vector machines for multivariate non-normal distributions (Q5086321) (← links)
• Support vector regression based residual control charts (Q5123523) (← links)
• Multivariate control chart based on the highest possibility region (Q5129064) (← links)
• A distribution-free multivariate CUSUM control chart using dynamic control limits (Q5138689) (← links)
• Comparison of Novelty Score-Based Multivariate Control Charts (Q5259156) (← links)
• A new control chart in contaminated data of <i>t</i>‐Student distribution for individual observations (Q5414528) (← links)
• A Comparative Study of Different Methodologies for Fault Diagnosis in Multivariate Quality Control (Q5415898) (← links)
• Multivariate Control Charts Based on Hybrid Novelty Scores (Q5417906) (← links)
• Kernel distance-based robust support vector methods and its application in developing a robust K-chart (Q5478816) (← links)
• An optimal control chart for finite matrix sequences at some unknown change point (Q5861597) (← links)
• Big Data? Statistical Process Control Can Help! (Q5869301) (← links)
• A phase I change‐point method for high‐dimensional process with sparse mean shifts (Q6054755) (← links)
• A Shewhart-type nonparametric multivariate depth-based control chart for monitoring location (Q6096198) (← links)
• Transparent Sequential Learning for Statistical Process Control of Serially Correlated Data (Q6631088) (← links)
• Statistical Process Monitoring from Industry 2.0 to Industry 4.0: Insights into Research and Practice (Q6637476) (← links)