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Control charts for monitoring the mean vector and the covariance matrix of bivariate processes
(Springer London Ltd, 2009-12-01)
In this article, we propose new control charts for monitoring the mean vector and the covariance matrix of bivariate processes. The traditional tools used for this purpose are the T (2) and the |S| charts. However, these ...
Monitoring the covariance matrix with the VMAX chart
(Int Soc Sci Appl Technol, 2008-01-01)
In this article, we propose a new statistic to control the covariance matrix of bivariate processes. This new statistic is based on the sample vat-lances of the two quality characteristics, shortly VMAX statistic. The ...
A single chart with supplementary runs rules for monitoring the mean vector and the covariance matrix of multivariate processes
(2013-08-15)
The MRMAX chart is a single chart based on the standardized sample means and sample ranges for monitoring the mean vector and the covariance matrix of multivariate processes. User's familiarity with the computation of these ...
Monitoring the covariance matrix with the vmax chart
(2008-12-01)
In this article, we propose a new statistic to control the covariance matrix of bivariate processes. This new statistic is based on the sample variances of the two quality characteristics, shortly VMAX statistic. The points ...
A bivariate generalized exponential distribution derived from copula functions in the presence of censored data and covariates
(2015-01-01)
In this paper, we introduce a Bayesian analysis for a bivariate generalized exponential distribution in the presence of censored data and covariates derived from Copula functions. The generalized exponential distribution ...
Covariational reasoning of university students in an approach to the concept of definite integral through Riemann sums
(Centro de Informacion Tecnologica, 2022-08-01)
This study aims to analyze changes in mental actions associated with the covariational reasoning of one pair of students when working on tasks to approach the concept of definite integral through Riemann sums. Mental actions ...
Assessing the estimation of nearly singular covariance matrices for modeling spatial variables
(Wiley, 2023)
© 2023, Institute of Mathematical Statistics. All rights reserved.Spatial analysis commonly relies on the estimation of a co-variance matrix associated with a random field. This estimation strongly impacts the prediction ...
Evolutionary transition between bee pollination and hummingbird pollination in Salvia: Comparing means, variances and covariances of corolla traits
(Wiley Blackwell Publishing, Inc, 2019-04)
Covariation among traits can modify the evolutionary trajectory of complex structures. This process is thought to operate at a microevolutionary scale, but its long-term effects remain controversial because trait covariation ...
Signal detection in high dimension: the multispiked case
(Inst Mathematical Statistics, 2014-02)
This paper applies Le Cam's asymptotic theory of statistical experiments to the signal detection problem in high dimension. We consider the problem of testing the null hypothesis of sphericity of a high-dimensional covariance ...
Covariance reducing models: An alternative to spectral modelling of covariance matrices
(Oxford University Press, 2008-12)
We introduce covariance reducing models for studying the sample covariance matrices of a random vector observed in different populations. The models are based on reducing the sample covariance matrices to an informational ...