Modification of Malinowski'sF-test for abstract factor analysis applied to the Quail Roost II data sets

Multivariate Chemometric Approach to Thermal Solid-State FT-IR Monitoring of Pharmaceutical Drug Compound

“…In order to determine the number of significant V T vectors, which is associated with the number of significant observable components in the system being studied, an F ‐test was performed on the generated singular values 19 . F ‐test predicted only four significant vectors, and thus the first four V T vectors were used for spectral reconstruction.…”

Resolve of overlapping voltammetric signals in using a wavelet packet transform based Elman recurrent neural network

“…Determining the number of factors is one of the most important steps in the factor-based methods. The essence of the step is the pseudo-rank determination of the raw experimental data [28]. Three principal factors for the case were selected on the basis of previous reported methods [14].…”

The determinants of long-run economic growth: A conceptually and computationally simple approach

“…Including only the information contained in the first r principal components of X 2 in the regression when the rank of X 2 is 5 In addition to the results reported in the paper the number of principal components has also been determined using the testing approaches of Lawley and Maxwell (1963), Malinowski (1989), Faber and Kowalski (1997), Schott (2006) and Kritchman and Nadler (2008). In a variety of simulations, however, the VPC criterion and a simple eigenvalue test based on the correlation matrix (see below) have performed best.…”