malinvaud: Malinvaud's test for significance of the CA dimensions
In CAinterprTools: Graphical Aid in Correspondence Analysis Interpretation and Significance Testings
Description
Usage
Arguments
Details
See Also
Examples
Description
This function allows you to perform the Malinvaud's test, which assesses the
significance of the CA dimensions.
Usage
1
Arguments
data
Name of the dataset (must be in dataframe format).
Details
The function returns both a table in the R console and a plot. The former
lists relevant information, among which the significance of each CA
dimension. The dot chart graphically represents the p-value of each dimension;
dimensions are grouped by level of significance; a red reference lines
indicates the 0.05 threshold.
See Also
Examples
1
2
3
4
5
data(greenacre_data)
#perform the Malinvaud test using the 'greenacre_data' dataset
#and store the output table in a object named 'res'
res <- malinvaud(greenacre_data)
CAinterprTools documentation built on July 8, 2020, 5:15 p.m.
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Description Usage Arguments Details See Also Examples
Description
This function allows you to perform the Malinvaud's test, which assesses the significance of the CA dimensions.
Usage
1 |
Arguments
data |
Name of the dataset (must be in dataframe format). |
Details
The function returns both a table in the R console and a plot. The former lists relevant information, among which the significance of each CA dimension. The dot chart graphically represents the p-value of each dimension; dimensions are grouped by level of significance; a red reference lines indicates the 0.05 threshold.
See Also
Examples
1 2 3 4 5 | data(greenacre_data)
#perform the Malinvaud test using the 'greenacre_data' dataset
#and store the output table in a object named 'res'
res <- malinvaud(greenacre_data)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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