summaryca: Summarise results

Description

Produces brief printed output of the usual correspondence analysis results for the first two dimensions of the solution, plus the standard deviations.

Usage

summaryca(x, datasetname = "")

Arguments

object of class cabootcrsresults

datasetname

name of data set, to appear in output

Value

Printed summary output.

Details

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

Examples

Run this code

# NOT RUN {
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")
  }
# }