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RedditHelp Ok so the general jacobian matrix of the system is given by h1 + 10h + hy −10h + hx i n n J= 30h + 2hxn 1 − 20h Now if we evaluate this matrix at the fixed point, then xn = 0 and yn = 0 giving us h1 + 10h −10h i J(0,0) = 30h 1 − 20h We need to find the eigenvalues of this matrix which are given by solving Determinant(J0,0 − λI) = 0 This gives us (1 + 10h − λ)(1 − 20h − λ) + 300h2 = 0 and expanding this out and solving for λ we get two solutions √ 1.
Minimum eigenvalues of 1.0 were used to determine the number of factors for each scale and with loading above 0.40 on a single factor was retained.
A natural way to robustify PCA is to use robust location and scatter estimators instead of the PCA's sample mean and sample covariance matrix when estimating the eigenvalues and eigenvectors of the population covariance matrix.