## S3 method for class 'corregp':
summary(object, parm = NULL, contrib = NULL, nf = NULL,
add_ci = FALSE, cl = 0.95, nq = TRUE, ...)corregp (i.e. an object of class "corregp").contrib. Can be either "y" for the Y contributions, "x" for the X contributions, "both"
which can be abbreviated to "b", or a vector of "pnts_to_axes" or "axes_to_pnts", "ptsFALSE.0.95.qnorm) in the computation of the confidence intervals.
Defaults to TRUE. If FALSE, then the confidence intervalsformulaformula specified to the formula argument in the call to corregp.datadata argument in the call to corregp.partpart argument in the call to corregp.chi_squaredphi_squaredN.Neigenadd_ci: if FALSE, a matrix of the actual eigenvalues, their percentages and cumulative percentages; if TRUE, a list of the actual eigenvalues, their percentages and cumulative percentages together with the lower and upper confidence limits for each.yparm is "y" or "b". A list of components p_a for the absolute contributions and//or a_p for the squared correlations, depending on contrib.xparm is "y", "b" or any of the term names in X. A list of components p_a for the absolute contributions and/or a_p for the squared correlations, depending in contrib.corregp, print.summary.corregp.data(HairEye)
haireye.crg <- corregp(Eye ~ Hair * Sex, data = HairEye, b = 3000)
summary(haireye.crg, add_ci = TRUE)
summary(haireye.crg, parm = "y", contrib = "pts_axs", nf = 2)Run the code above in your browser using DataLab