この節の作者: Ravi Selker, Jonathon Love, Damian Dropmann
Principal Component Analysis (pca
)¶
Description¶
Principal Component Analysis
Usage¶
pca(
data,
vars,
nFactorMethod = "parallel",
nFactors = 1,
minEigen = 1,
rotation = "varimax",
hideLoadings = 0.3,
sortLoadings = FALSE,
screePlot = FALSE,
eigen = FALSE,
factorCor = FALSE,
factorSummary = FALSE,
kmo = FALSE,
bartlett = FALSE
)
Arguments¶
data |
the data as a data frame |
vars |
a vector of strings naming the variables of
interest in data |
nFactorMethod |
'parallel' (default), 'eigen' or
'fixed' , the way to determine the number of
factors |
nFactors |
an integer (default: 1), the number of components in the model |
minEigen |
a number (default: 1), the minimal eigenvalue for a component to be included in the model |
rotation |
'none' , 'varimax' (default),
'quartimax' , 'promax' , 'oblimin' ,
or 'simplimax' , the rotation to use in
estimation |
hideLoadings |
a number (default: 0.3), hide loadings below this value |
sortLoadings |
TRUE or FALSE (default), sort the
factor loadings by size |
screePlot |
TRUE or FALSE (default), show scree
plot |
eigen |
TRUE or FALSE (default), show
eigenvalue table |
factorCor |
TRUE or FALSE (default), show factor
correlations |
factorSummary |
TRUE or FALSE (default), show factor
summary |
kmo |
TRUE or FALSE (default), show
Kaiser-Meyer-Olkin (KMO) measure of sampling
adequacy (MSA) results |
bartlett |
TRUE or FALSE (default), show
Bartlett's test of sphericity results |
Output¶
A results object containing:
results$loadings |
a table |
results$factorStats$factorSummary |
a table |
results$factorStats$factorCor |
a table |
results$modelFit$fit |
a table |
results$assump$bartlett |
a table |
results$assump$kmo |
a table |
results$eigen$initEigen |
a table |
results$eigen$screePlot |
an image |
Tables can be converted to data frames with asDF
or
as.data.frame()
. For example:
results$loadings$asDF
as.data.frame(results$loadings)
Examples¶
data('iris')
pca(iris, vars = vars(Sepal.Length, Sepal.Width, Petal.Length, Petal.Width))
#
# PRINCIPAL COMPONENT ANALYSIS
#
# Component Loadings
# ----------------------------------------
# 1 Uniqueness
# ----------------------------------------
# Sepal.Length 0.890 0.2076
# Sepal.Width -0.460 0.7883
# Petal.Length 0.992 0.0168
# Petal.Width 0.965 0.0688
# ----------------------------------------
# Note. 'varimax' rotation was used
#