In usual quality control methods, the of a process or product is evaluated by monitoring one more characteristics using their corresponding distributions. However, when characteristic defined through relationship between response and independent variables, regime referred to as profiles monitoring. this article, we improve performance Exponentially Weighted Moving Average Range (EWMAR) charts, ...

We introduce a covariance matrix estimator that both takes into account the heteroskedasticity of financial returns (by using an exponentially weighted moving average) and reduces the effective dimensionality of the estimation (and hence measurement noise) via techniques borrowed from random matrix theory. We calculate the spectrum of large exponentially weighted random matrices (whose upper ba...

Online monitoring of the multivariate coefficient variation (MCV) can be interest in many real situations which dispersion a process is meant to remain constant with regard its position. To this aim, several control charts have been recently proposed literature. In paper, new one-sided adaptive monitor MCV are proposed. The chart applies variable sampling interval (VSI) strategy on an exponenti...

A quality-control chart based on exponentially weighted moving averages (EWMA) has, in the past few years, become a popular tool for controlling inaccuracy in industrial quality control. In this paper, I explain the principles of this technique, present some numerical examples, and by computer simulation compare EWMA with other control charts currently used in clinical chemistry. The EWMA chart...

Multivariate control charts are very effective when monitoring several correlated characteristics. Proper process control consists of monitoring both mean and variability. In multivariate settings, the multivariate exponentially weighted moving average (MEWMA) is ideal to monitor the mean vector. Similarly, the recently-proposed multivariate exponentially weighted moving covariance matrix (MEWM...

The control limits of an exponentially weighted moving average (EWMA) control chart should vary with time, approaching asymptotic limits as time increases. However, previous analytic analyses of EWMA charts consider only asymptotic control limits. In this article, the run length properties of EWMAs with time-varying control limits are approximated using nonhomogeneous Markov chains. Comparing t...

The geometric-Poisson exponentially weighted moving average (EWMA) chart has been shown to be more effective than the Poisson EWMA chart in monitoring the number of defects in the production processes. In these applications, it is assumed that the process parameters are known or have been accurately estimated. However, in practice, the process parameters are rarely known and must be estimated f...

The principal component analysis (PCA) is a staple statistical and unsupervised machine learning technique in finance. application of PCA financial setting associated with several difficulties, such as numerical instability nonstationarity. We attempt to resolve them by proposing two new variants PCA: an iterated (IPCA) exponentially weighted moving (EWMPCA). Both rely on the Ogita-Aishima iter...

Abstract:
 In many real-world applications, the data to be used in a control charting method are not crisp since they approximated due environmental uncertainties, these situations, fuzzy numbers and linguistic variables grab such uncertainties. That is why use of chart, which used, justified. As an exponentially weighted moving average (EWMA) scheme usually detect small shifts, this paper ...