rSCA (version 2.1)

rSCA.correlation: Correlation Analysis for Modeling Data Sets

Description

This function aims to analyze the correlations between dependent and independent variables. It prints out a table consisting of the correlation coefficient for each pair of dependent and independent variables.

Usage

rSCA.correlation(xfile, yfile, x.row.names = FALSE, x.col.names = FALSE, 
        y.row.names = FALSE, y.col.names = FALSE, x.missing.flag = "NA", 
        y.missing.flag = "NA", x.type = ".txt", y.type = ".txt")

Arguments

xfile

a string to specify the path to the data file of the independent variables (X), only supports files in two formats: *.txt or *.csv.

yfile

a string to specify the path to the data file of the dependent variables (Y), only supports files in two formats: *.txt or *.csv.

x.row.names

a logical value to specify if the independent (X) data file contains row names or not. Default value is FALSE.

x.col.names

a logical value to specify if the independent (X) data file contains column names or not. Default value is FALSE.

y.row.names

a logical value to specify if the dependent (Y) data file contains row names or not. Default value is FALSE.

y.col.names

a logical value to specify if the dependent (Y) data file contains column names or not. Default value is FALSE.

x.missing.flag

a string to specify the missing flag used in the independent (X) data file. Default value is "NA".

y.missing.flag

a string to specify the missing flag used in the dependent (Y) data file. Default value is "NA".

x.type

a string to specify the type of independent (X) data file. Default value is ".txt".

y.type

a string to specify the type of dependent (Y) data file. Default value is ".txt".

Examples

Run this code
# NOT RUN {
## Load rSCA package
library(rSCA)

## X data file
xdata <- c("A B C D\r", "0.095 0.044 39.9 27\r", 
           "0.810 0.058 9.1 8\r", "0.101 0.077 11.4 14\r",
           "0.006 0.141 20.5 29\r", "0.070 0.281 27.3 26\r",
           "0.481 0.514 30.2 48\r", "0.120 0.286 36.4 39\r",
           "0.480 0.199 40.9 27\r", "0.112 0.101 29.9 18\r",
           "0.026 0.203 48.1 28\r", "0.128 1.235 48.2 61\r",
           "2.681 0.439 51.1 98\r", "1.601 0.333 56.1 99\r",
           "1.398 0.455 19.3 103\r", "1.256 0.314 14.9 17\r",
           "2.618 0.609 9.1 19\r", "1.217 0.880 17.2 73\r",
           "1.411 2.115 19.6 203\r", "0.245 6.839 49.2 296\r",
           "0.724 3.060 17.1 192\r", "0.019 2.252 29.1 123\r",
           "1.321 5.730 41.1 288\r", "0.903 3.078 39.0 97\r",
           "0.714 1.013 16.7 5\r", "0.581 1.398 11.7 57\r",
           "0.080 1.734 10.2 52\r", "0.120 1.848 6.6 132\r",
           "0.089 1.357 10.3 148\r", "0.112 0.585 19.3 79\r",
           "0.192 0.675 6.9 39\r", "0.301 1.937 11.9 6\r")
xdatafile <- tempfile()
writeLines(xdata, xdatafile)

## Y data file
ydata <- c("Y1 Y2 Y3\r", "0.020 0.034 10.01\r",
           "0.011 0.011 6.92\r", "0.016 0.018 9.53\r",
           "0.022 0.018 5.04\r", "0.031 0.029 8.90\r",
           "0.057 0.036 9.98\r", "0.040 0.048 12.96\r",
           "0.061 0.050 9.84\r", "0.023 0.031 8.84\r",
           "0.025 0.020 4.66\r", "0.041 0.042 9.02\r",
           "0.070 0.029 11.37\r", "0.077 0.022 11.88\r",
           "0.105 0.038 11.06\r", "0.038 0.027 11.64\r",
           "0.058 0.019 8.25\r", "0.051 0.050 10.01\r",
           "0.073 0.038 9.20\r", "0.123 0.080 9.91\r",
           "0.089 0.046 9.37\r", "0.073 0.039 7.99\r",
           "0.139 0.069 13.28\r", "0.095 0.048 9.80\r",
           "0.034 0.040 8.50\r", "0.055 0.034 9.21\r",
           "0.020 0.050 8.67\r", "0.070 0.036 8.03\r",
           "0.058 0.039 8.01\r", "0.057 0.031 6.30\r",
           "0.050 0.014 7.92\r", "0.039 0.040 8.08\r")
ydatafile <- tempfile()
writeLines(ydata, ydatafile)

## Analyze correlations between y and x
rSCA.correlation(xfile = xdatafile, x.col.names = TRUE,
    yfile = ydatafile, y.col.names = TRUE)

## Remove temporary data files
unlink(xdatafile)
unlink(ydatafile)
# }

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