Giovanni Zurlini
A PCA is made for reducing the dimensions of data sets through orthogonal (independent) axes of variation, so PC1 must account for a higher variance than PC2, which will be smaller than PC3 and so on..However if you have a data set with lots of zero counts you can have problem when applying the routine HOW for calculating the determinant of the matrix. Is that your case?
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Agung Dhamar Syakti
Dear Giovanni,
Indeed, thanks for your response, I have re-checked the data and obviously there is an error due to my wrong data entry when i ran the software.
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Azubuike Victor Chukwuka
Very true, PC 1 must account for a higher variance than PC 2 and so on. Its good you've confirmed the problem in your data entry.
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