Multivariate Quality Control Using Finite Intersection Tests

Multivariate quality control problems involve the evaluation of a process based on the simultaneous behavior of p variables. Most multivariate quality control procedures evaluate the in-control or out-of-control condition based upon an overall statistic..

[1]  J. V. Armitage,et al.  Tables for the distribution of the maximum of correlated chi-square variates with one degree of freedom , 1965 .

[2]  J. Edward Jackson,et al.  Principal Components and Factor Analysis: Part I - Principal Components , 1980 .

[3]  J. Healy.  A note on multivariate CUSUM procedures , 1987 .

[4]  S. J. Wierda.  Multivariate statistical process control—recent results and directions for future research , 1994 .

[5]  Peter R. Nelson,et al.  Additional Uses for the Analysis of Means and Extended Tables of Critical Values , 1993 .

[6]  J. Jackson,et al.  An Application of Multivariate Quality Control to Photographic Processing , 1957 .

[7]  H. Scheffé.  A Note on a Reformulation of the S-Method of Multiple Comparison , 1977 .

[8]  William H. Woodall,et al.  A review and analysis of cause-selecting control charts , 1993 .

[9]  Douglas M. Hawkins,et al.  Regression Adjustment for Variables in Multivariate Quality Control , 1993 .

[10]  K. Tsui,et al.  Identification and Quantification in Multivariate Quality Control Problems , 1994 .

[11]  Anthony J. Hayter,et al.  On the Relationship between Stepwise Decision Procedures and Confidence Sets , 1994 .

[12]  Nola D. Tracy,et al.  Decomposition of T2 for Multivariate Control Chart Interpretation , 1995 .

[13]  J. Roy,et al.  STEP-DOWN PROCEDURE IN MULTIVARIATE ANALYSIS , 1958 .

[14]  J. Troendle,et al.  A Stepwise Resampling Method of Multiple Hypothesis Testing , 1995 .

[15]  P. Krishnaiah,et al.  On the simultaneous anova and manova tests , 1965 .