Description Details Objects from the Class Slots Methods Author(s) See Also Examples
It is not necessary to understand this help page if one merely wants to estimate a factor analysis model. This help page is intended for those who want to modify or extend FAiR or otherwise want some idea of how FAiR works “behind the scenes”.
This class contains information in its slots about the left-hand side of a factor analysis model.
In the future, the advantages of formal S4 classes will be exploited more fully. For
example, to include a new model in FAiR, the first step might be to define a
a new class that extends "manifest"
if necessary. Then, appropriate methods for
this class would need to be written. Here is a table of the class hierarchy:
Class | Parent Class | Comment |
"manifest" | none | none (virtual class) |
"manifest.basic" | "manifest" | Can be used for any model |
"manifest.basic.userW" | "manifest.basic" | ADF with user-specified weight matrix |
"manifest.data" | "manifest.basic" | Can be used for any model |
"manifest.data.ordinal" | "manifest.data" | Used when some variables are ordinal |
"manifest.data.ranks" | "manifest.data" | Used when variables are converted to their ranks |
"manifest.data.mcd" | "manifest.data" | Can be used for any model |
Objects can be created by calls of the form new("manifest", ...)
.
However, it is not recommended to do so in normal usage since
make_manifest
provides the constructor for users.
The "manifest"
is virtual and has the following slots:
An integer indicating the number of observations.
A character string indicating how the covariance matrix among the manifest variables was calculated.
The call to make_manifest
.
An object of class "manifest.basic"
inherits from the "manifest"
class and has five additional slots:
A sample covariance matrix among manifest variables.
A sample correlation matrix among manifest variables.
A numeric vector containing the square root of the diagonal of the sample covariance matrix.
A numeric vector containing the mean of the manifest variables.
A logical indicating whether the diagonal elements of the sample “covariance” matrix are all 1.0.
An object of class "manifest.data"
inherits from the "manifest.basic"
class and and has four additional slots:
A numeric matrix of manifest variables (unstandardized).
A numeric vector whose length is the same as the number of rows
in X
indicating the weight of each observation in calculating the
sample covariance matrix.
An object of dsyMatrix-class
from the Matrix
package representing an asymptotic estimate of the fourth-order central moments of
the data
An object of class "manifest.data.ordinal"
inherits from the "manifest.data"
but has no additional slots. It is used when some of the manifest variables are ordered
factors. Likewise for the "manifest.data.ranks"
class which has no additional
slots and is used when Spearman correlations are calculated. An object of class
"manifest.data.mcd"
inherits from the "manifest.data"
class and has one
additional slot, CovMcd
, which is an object of CovMcd-class
that is defined in the rrcov package.
Technically, "manifest"
is in the signature of all the model-fitting generic
functions documented in S4GenericsFAiR
and the same is true for
make_restrictions
However, at the moment those methods are only defined
for the "manifest.basic"
class. The following methods are defined for the
"manifest.basic"
class, but some of them are also defined for inherited classes
if their behavior needs to differ in small ways.
signature(object = "manifest.basic")
signature(object = "manifest.basic")
, which also has
a standardized = TRUE
argument that controls whether the sample
correlation matrix or sample covariance matrix is extracted
signature(object = "manifest.basic")
signature(x = "manifest.basic", y = "ANY")
signature(x = "manifest.basic")
Ben Goodrich
make_manifest
and S4GenericsFAiR
1 2 3 4 5 6 7 8 | showClass("manifest")
showClass("manifest.basic")
showClass("manifest.data")
showClass("manifest.data.mcd")
man <- make_manifest(covmat = Harman74.cor)
show(man)
plot(man)
str(man)
|
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