Description Usage Arguments Examples

Uses the eigendecomposition of a square, symmetrix matrix R to obtain the
loadings matrix L such that R is approximated by LL', with L restricted to
have `r`

columns. Hence LL' is a rank `r`

approximation of R. The
eigendecomposition of R is used to obtain L from the first `r`

eigenvectors and eigenvalues. In case `procr.target`

is not
`NULL`

, L is further rotated through orthogonal Procrustes analysis to
match as closely as possible the matrix `procr.target`

through
`orthprocr`

.

1 | ```
approxloads(R, r = 3, procr.target = NULL, refl.target = NULL)
``` |

`R` |
Square, symmetric matrix R to be approximated |

`r` |
The required rank of the approximation |

`procr.target` |
Optional; the target matrix for L in the orthogonal Procrustes analysis |

`refl.target` |
Optional; the matrix to check against for possible reflections of the loading vectors. |

1 2 | ```
R <- rcormat(10, r = 3)
all.equal(R$L, approxloads(R$R, r = 3, procr.target = R$L))
``` |

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