Print an object of class can_cor object in two ways. By default, the
results are shown in the R console. The results can also be exported to the
directory.
Usage
# S3 method for can_cor
print(x, export = FALSE, file.name = NULL, digits = 3, ...)Arguments
- x
An object of class
can_cor.- export
A logical argument. If
TRUE|T, a *.txt file is exported to the working directory- file.name
The name of the file if
export = TRUE- digits
The significant digits to be shown.
- ...
Options used by the tibble package to format the output. See
tibble::print()for more details.
Author
Tiago Olivoto tiagoolivoto@gmail.com
Examples
# \donttest{
library(metan)
cc <- can_corr(data_ge2,
FG = c(PH, EH, EP),
SG = c(EL, CL, CD, CW, KW, NR, TKW),
verbose = FALSE)
print(cc)
#> ---------------------------------------------------------------------------
#> Matrix (correlation/covariance) between variables of first group (FG)
#> ---------------------------------------------------------------------------
#> PH EH EP
#> PH 1.000 0.932 0.638
#> EH 0.932 1.000 0.870
#> EP 0.638 0.870 1.000
#>
#> ---------------------------------------------------------------------------
#> Collinearity diagnostic between first group
#> ---------------------------------------------------------------------------
#> The multicollinearity in the matrix should be investigated.
#> CN = 977.586
#> Largest VIF = 229.164618380199
#> Matrix determinant: 0.0025852
#> Largest correlation: PH x EH = 0.932
#> Smallest correlation: PH x EP = 0.638
#> Number of VIFs > 10: 3
#> Number of correlations with r >= |0.8|: 2
#> Variables with largest weight in the last eigenvalues:
#> EH > PH > EP
#>
#> ---------------------------------------------------------------------------
#> Matrix (correlation/covariance) between variables of second group (SG)
#> ---------------------------------------------------------------------------
#> EL CL CD CW KW NR TKW
#> EL 1.0000 0.255 0.9119 0.458 0.669 -0.0139 0.442
#> CL 0.2554 1.000 0.3004 0.738 0.471 0.2619 0.619
#> CD 0.9119 0.300 1.0000 0.484 0.626 -0.0358 0.443
#> CW 0.4582 0.738 0.4840 1.000 0.735 0.1657 0.673
#> KW 0.6686 0.471 0.6260 0.735 1.000 0.3621 0.673
#> NR -0.0139 0.262 -0.0358 0.166 0.362 1.0000 -0.109
#> TKW 0.4421 0.619 0.4433 0.673 0.673 -0.1088 1.000
#>
#> ---------------------------------------------------------------------------
#> Collinearity diagnostic between second group
#> ---------------------------------------------------------------------------
#> Weak multicollinearity in the matrix
#> CN = 66.912
#> Matrix determinant: 0.0026584
#> Largest correlation: EL x CD = 0.912
#> Smallest correlation: EL x NR = -0.014
#> Number of VIFs > 10: 0
#> Number of correlations with r >= |0.8|: 1
#> Variables with largest weight in the last eigenvalues:
#> KW > TKW > EL > CW > CL > NR > CD
#>
#> ---------------------------------------------------------------------------
#> Matrix (correlation/covariance) between FG and SG)
#> ---------------------------------------------------------------------------
#> EL CL CD CW KW NR TKW
#> PH 0.380 0.325 0.315 0.505 0.753 0.329 0.569
#> EH 0.363 0.397 0.281 0.519 0.703 0.265 0.562
#> EP 0.263 0.391 0.175 0.425 0.497 0.140 0.426
#>
#> ---------------------------------------------------------------------------
#> Correlation of the canonical pairs and hypothesis testing
#> ---------------------------------------------------------------------------
#> Var Percent Sum Corr Lambda Chisq DF p_val
#> U1V1 0.6500 74.35 74.4 0.806 0.273 194.28 21 0e+00
#> U2V2 0.2087 23.87 98.2 0.457 0.779 37.33 12 2e-04
#> U3V3 0.0156 1.78 100.0 0.125 0.984 2.35 5 8e-01
#>
#> ---------------------------------------------------------------------------
#> Canonical coefficients of the first group
#> ---------------------------------------------------------------------------
#> U1 U2 U3
#> PH 2.66 5.26 7.72
#> EH -2.58 -7.33 -12.99
#> EP 1.15 2.27 6.67
#>
#> ---------------------------------------------------------------------------
#> Canonical coefficients of the second group
#> ---------------------------------------------------------------------------
#> V1 V2 V3
#> EL -0.00776 -0.832 0.4561
#> CL -0.25837 -1.430 0.1989
#> CD -0.23630 1.177 -1.1116
#> CW -0.06101 0.338 0.0822
#> KW 0.91468 -0.691 1.4550
#> NR 0.21616 0.914 -0.5313
#> TKW 0.39749 0.717 -1.5248
# }