![]() ![]() ![]() independent variables) should be used to build the PCA. ![]() The set of dependent variables should be used here as a set of supplementary variables and the others (i.e. If the user wants to investigate roughly how a set of dependent variables relates to the others.Those variables or observations are called supplementary. XLSTAT lets you add variables (qualitative or quantitative) or observations to the PCA after it has been computed. PCA with supplementary variables and observations ![]() Where only a similarity matrix is available rather than a table of observations/variables, or where you want to use another similarity index, you can carry out a PCA starting from the similarity matrix (correlation or covariance). However in certain areas, when the variables are supposed to be on an identical scale or we want the variance of the variables to influence factor building, covariance is used. Traditionally, a correlation coefficient rather than the covariance is used as using a correlation coefficient removes the effect of scale: thus a variable which varies between 0 and 1 does not weigh more in the projection than a variable varying between.
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