Description Usage Arguments Details Value Author(s)
Perform a principal component analysis to recover the module structure of a cloned network.
1 |
data |
Matrix of numerics. The data file. |
N |
Integer. The dimension of the original network. Only relevant if |
assignments |
Vector of integers. The correct clustering to recover, the output of function |
around |
Integer. If |
rep |
Integer. Iterations for parallel analysis. |
quantile |
Numeric in [0,1]. Quantile for the parallel analysis. Conventional values are .95 or .99. |
rotate |
Character string. The kind of rotation. An "oblimin" rotation is suggested. |
stoppingrule |
Vector of strings. Specify the stopping rule to determine the number of components. Can include one or more methods among |
The function performs a principal component analysis. Once the PCA is performed, each node is assigned to a module according to its highest component loading.
The number of components can be determined in three ways. If "easystop"
is included in stoppinngrule
, the correct number of factors (as specified by N
) are kept. If "parallel"
is included in stoppingrule
, the number of components is determined using parallel analysis. If mehod "optimal"
is included in stoppingrule
, several numbers of factors are considered in the surroundings of N
, from N-around
to N+around
. The number of factors that results in the best adjusted Rand index is retained (see adjustedRandIndex
).
Matrix of integers. A row for each cloned node (= a row for each column of the input matrix data
), a column for each stopping rule. An integer indicates the belonging of each node to a module. Consider that the choice of the numbers is arbitrary, they are on a nominal scale. The only important thing is whether two nodes are in the same module or not.
Giulio Costantini
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