summaryca {cabootcrs} | R Documentation |
Produces brief printed output of the usual correspondence analysis results for the first two dimensions of the solution, plus the standard deviations.
summaryca(x, datasetname = "")
x |
object of class cabootcrsresults |
datasetname |
name of data set, to appear in output |
Gives the principal inertias for all dimensions, followed by, for rows and then columns:
Principal coordinate, first axis
Standard deviation, first axis
Representation, a.k.a. correlation (per mil), first axis
Contribution (per mil), first axis
Principal coordinate, second axis
Standard deviation, second axis
Representation (per mil), second axis
Contribution (per mil), second axis
Representation, a.k.a. correlation (per mil), first two axes
Printed summary output.
T.J. Ringrose
printca
,
plotca
,
cabootcrsresults
dreamdata <- t(matrix(c(7,4,3,7,10,15,11,13,23,9,11,7,28,9,12,10,32,5,4,3),4,5)) bd <- cabootcrs(dreamdata) summaryca(bd, datasetname="Dreams") ## The function is currently defined as function (x, datasetname = "") { colnames <- character(length = 9) colnames <- c(" Axis 1", "StDev", "Rep", "Ctr", " Axis 2", "StDev", "Rep", "Ctr", "Quality") colnamesnosd <- character(length = 7) colnamesnosd <- c(" Axis 1", "Rep", "Ctr", " Axis 2", "Rep", "Ctr", "Quality") cat("\n SUMMARY RESULTS for Correspondence Analysis:", datasetname, "\n\n") cat("Total inertia ", x@inertiasum, "\n\n") cat("Inertias, percent inertias and cumulative percent inertias \n\n") ins <- data.frame(x@inertias) names(ins) <- c("Inertia", "% ", "Cum. %") print(ins, digits = 4) cat("\n") if (x@nboots > 0) { cat("Princ coords, std devs; rep and ctr (per mil); 2-d rep (per mil)\n\n") } else { cat("Princ coords; rep and ctr (per mil); 2-d rep (per mil)\n\n") } cat("Rows: \n") rop <- data.frame(round(x@Rowprinccoord[, 1] * 1000)/1000, round(sqrt(x@RowVar[, 1]) * 1000)/1000, round(x@RowREP[, 1] * 1000), round(x@RowCTR[, 1] * 1000), round(x@Rowprinccoord[, 2] * 1000)/1000, round(sqrt(x@RowVar[, 2]) * 1000)/1000, round(x@RowREP[, 2] * 1000), round(x@RowCTR[, 2] * 1000), round(rowSums(x@RowREP[, 1:2] * 1000)), row.names = x@rowlabels) if (x@nboots == 0) { rop <- rop[, c(1, 3, 4, 5, 7, 8, 9)] names(rop) <- colnamesnosd } else { names(rop) <- colnames } print(rop, digits = 3) cat("\n") cat("Columns: \n") cop <- data.frame(round(x@Colprinccoord[, 1] * 1000)/1000, round(sqrt(x@ColVar[, 1]) * 1000)/1000, round(x@ColREP[, 1] * 1000), round(x@ColCTR[, 1] * 1000), round(x@Colprinccoord[, 2] * 1000)/1000, round(sqrt(x@ColVar[, 2]) * 1000)/1000, round(x@ColREP[, 2] * 1000), round(x@ColCTR[, 2] * 1000), round(rowSums(x@ColREP[, 1:2] * 1000)), row.names = x@collabels) if (x@nboots == 0) { cop <- cop[, c(1, 3, 4, 5, 7, 8, 9)] names(cop) <- colnamesnosd } else { names(cop) <- colnames } print(cop, digits = 3) cat("\n") }