×

Estimation of the confidence limits for the quadratic forms in normal variables using a simple Gaussian distribution approximation. (English) Zbl 1091.62004

The distribution of a quadratic form \(Q=\sum_{k=1}^n d_k y_k^2\), where \(y_k\) are i.i.d. standard Gaussian variables, is approximated by \({\mathcal N}(\sum_{k=1}^n d_k, 2\sum_{k=1}^n d_k^2)\). The related approximation for quantiles of \(Q\) (one-sided confidence bounds) is analysed via simulations. E.g., it is noted that for \(n=100\) the relative error of such approximation is less then 7%.

MSC:

62E17 Approximations to statistical distributions (nonasymptotic)
62-08 Computational methods for problems pertaining to statistics
62E20 Asymptotic distribution theory in statistics
62F25 Parametric tolerance and confidence regions
Full Text: DOI

References:

[1] Box, G. E. P. (1954),‘Some theorems on quadratic forms applied in the study of analysis of variance problems: Effect of inequality of variance in one-way classification’The Annals of Mathematical Statistics25, 290-302. · Zbl 0055.37305 · doi:10.1214/aoms/1177728786
[2] Durrett, R. (1996),Probability: Theory and Applications, Wadsworth, Belmont.
[3] Imhof, J. P. (1961),‘Computing the distribution of quadratic forms in normal variables’Biometrika48 (4), 419-426. · Zbl 0136.41103 · doi:10.1093/biomet/48.3-4.419
[4] Jackson, J.E. & Mudholkar, G. S. (1979),‘Control procedures for residuals associated with principal Component Analysis’Technometrics21 (3), 341-349. · Zbl 0439.62039 · doi:10.1080/00401706.1979.10489779
[5] Jensen, D.R. & Solomon, H. (1972),‘A Gaussian approximation to the distribution of a definite quadratic Form’Journal of American Statistical Association67 (340), 898-902. · Zbl 0254.62013
[6] Juricic, D. & Žele, M. (2002),‘Robust detection of sensor faults by means of a statistical test’Automatica (Oxf.)38, 737-742. · Zbl 1006.94036 · doi:10.1016/S0005-1098(01)00256-4
[7] Kotz, S., Johnson, N. L. & Boyd, D. W. (1967),‘Series representation distribution of quadratic forms in normal variables: I. Central case’The Annals of Mathematical Statistics38, 832-848. · Zbl 0146.40906
[8] Nomikos, P. & MacGregor, J. F. (1995),‘Multivariate SPC Charts for monitoring batch processes’Technometrics37 (1), 41-59. · Zbl 0825.62740 · doi:10.1080/00401706.1995.10485888
[9] Rohatgi, V.K. (1976)An Introduction to Probability Theory and Mathematical Statistics, New York: John Wiley and Sons. · Zbl 0354.62001
[10] Wise, B. M., Ricker, N. L., Veltkamp, D. F. & Kowalski, B. R. (1990),‘A theoretical basis for the use of principal component models for monitoring multivariate processes’Process and control quality1, 41-51.
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.