Sentences with phrase «eigenvalues >»

Results from the exploratory factor analysis indicated that eight items loaded on two factors (only two factors had eigenvalues > 1.0).

In the PCA, three components with eigenvalues > 1 were extracted from the data set.

However, the six factors were originally selected by the Kaiser - Guttman rule (eigenvalue > 1), which is not recommended for determining the number of factors [24] for the following reasons; First, this method is recommended for the principal component analysis (PCA) case and not for the EFA.

Factors with an eigenvalue > 1.0 were selected.

For each scale, two factors with an eigenvalue > 1.0 were identified.

Not exact matches

c now determine suggested number of EOFs in training c based on rule N applied to the proxy data alone c during the interval t > iproxmin (the minimum c year by which each proxy is required to have started, c note that default is iproxmin = 1820 if variable c proxy network is allowed (latest begin date c in network) c c we seek the n first eigenvectors whose eigenvalues c exceed 1 / nproxy» c c nproxy» is the effective climatic spatial degrees of freedom c spanned by the proxy network (typically an appropriate c estimate is 20 - 40)