brStick: Broken-stick method for detection of significant factors
In CENFA: Climate and Ecological Niche Factor Analysis
Description
Usage
Arguments
Value
References
Examples
Description
This function provides a simple way to determine the number of significant
factors in a factor analysis. This is done by comparing the eigenvalues of
each factor with those expected from a broken-stick distribution.
Usage
1
brStick(eigs)
Arguments
eigs
numeric. Vector of eigenvalues
Value
Returns the number of significant factors.
References
Jackson, Donald A. "Stopping rules in principal components analysis:
a comparison of heuristical and statistical approaches." Ecology 74.8 (1993):
2204-2214.
Examples
1
2
mod1 <- enfa(x = climdat.hist, s.dat = ABPR, field = "CODE")
brStick(s.factor(mod1))
CENFA documentation built on Aug. 16, 2021, 9:06 a.m.
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Description Usage Arguments Value References Examples
Description
This function provides a simple way to determine the number of significant factors in a factor analysis. This is done by comparing the eigenvalues of each factor with those expected from a broken-stick distribution.
Usage
1 | brStick(eigs)
|
Arguments
eigs |
numeric. Vector of eigenvalues |
Value
Returns the number of significant factors.
References
Jackson, Donald A. "Stopping rules in principal components analysis: a comparison of heuristical and statistical approaches." Ecology 74.8 (1993): 2204-2214.
Examples
1 2 | mod1 <- enfa(x = climdat.hist, s.dat = ABPR, field = "CODE")
brStick(s.factor(mod1))
|
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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