eigs_sym.undirected_factor_model {fastRG} | R Documentation |
Compute the eigendecomposition of the expected adjacency matrix of an undirected factor model
Description
Compute the eigendecomposition of the expected adjacency matrix of an undirected factor model
Usage
## S3 method for class 'undirected_factor_model'
eigs_sym(A, k = A$k, which = "LM", sigma = NULL, opts = list(), ...)
Arguments
A |
|
k |
Desired rank of decomposition. |
which |
Selection criterion. See Details below. |
sigma |
Shift parameter. See section Shift-And-Invert Mode. |
opts |
Control parameters related to the computing algorithm. See Details below. |
... |
Unused, included only for consistency with generic signature. |
Details
The which
argument is a character string
that specifies the type of eigenvalues to be computed.
Possible values are:
"LM" | The eigenvalues with largest magnitude. Here the
magnitude means the Euclidean norm of complex numbers. |
"SM" | The eigenvalues with smallest magnitude. |
"LR" | The eigenvalues with largest real part. |
"SR" | The eigenvalues with smallest real part. |
"LI" | The eigenvalues with largest imaginary part. |
"SI" | The eigenvalues with smallest imaginary part. |
"LA" | The largest (algebraic) eigenvalues, considering any
negative sign. |
"SA" | The smallest (algebraic) eigenvalues, considering any
negative sign. |
"BE" | Compute eigenvalues, half from each end of the
spectrum. When is odd, compute more from the high
and then from the low end.
|
eigs()
with matrix types "matrix", "dgeMatrix", "dgCMatrix"
and "dgRMatrix" can use "LM", "SM", "LR", "SR", "LI" and "SI".
eigs_sym()
with all supported matrix types,
and eigs()
with symmetric matrix types
("dsyMatrix", "dsCMatrix", and "dsRMatrix") can use "LM", "SM", "LA", "SA" and "BE".
The opts
argument is a list that can supply any of the
following parameters:
ncv
Number of Lanzcos basis vectors to use. More vectors will result in faster convergence, but with greater memory use. For general matrix,
ncv
must satisfy, and for symmetric matrix, the constraint is
. Default is
min(n, max(2*k+1, 20))
.tol
Precision parameter. Default is 1e-10.
maxitr
Maximum number of iterations. Default is 1000.
retvec
Whether to compute eigenvectors. If FALSE, only calculate and return eigenvalues.
initvec
Initial vector of length
supplied to the Arnoldi/Lanczos iteration. It may speed up the convergence if
initvec
is close to an eigenvector of.