Dynamic Multivariate Statistical Process Control using Subspace Identification

This paper points out a serious flaw in dynamic multivariate statistical process control (MSPC). The principal component analysis of a linear time series model that is employed to capture auto- and cross-correlation in recorded data may produce a considerable number of variables to be analysed. To give a dynamic representation of the data (based on variable correlation) and circumvent the production of a large time-series structure, a linear state space model is used here instead. The paper demonstrates that incorporating a state space model, the number of variables to be analysed dynamically can be considerably reduced, compared to conventional dynamic MSPC techniques.

The Apperceptive Personality Test located in personality space.

The Apperceptive Personality Test is a projective test that claims to show good psychometric properties but which has not been related to the main, Eysenckian, personality traits. This study investigated the overlap between these two tests using a sample of students. Correlational and regression analyses showed a modest degree of overlap between Extraversion, Neuroticism and some of the scales from the Apperceptive Personality Test.