Description Usage Arguments Details Author(s) Examples

Compute the Fraction of Standard Deviation (FSD) of two univariate signals Y (imputed values) and X (true values).

1 | ```
compute.fsd(Y, X, verbose = F)
``` |

`Y` |
vector of imputed values |

`X` |
vector of true values |

`verbose` |
if TRUE, print advice about the quality of the model |

This function returns the FSD value between two univariate signals. FSD value approaches zero means that a better performance method for the imputation task. Y and X must have the same length, conversely an error will be appeared. In both input vectors, NA will be exluded with a warning diplayed.

Thi-Thu-Hong Phan, Andre Bigand, Emilie Poisson-Caillault

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ```
data(dataFSMUMI)
X <- dataFSMUMI[, 1] ; Y <- dataFSMUMI[, 2]
compute.fsd(Y,X)
compute.fsd(Y,X, verbose = TRUE)
# By definition, if true and imputed values are equal and constant,
# FSD = 0.
X <- rep(runif(1), 10)
Y <- X
compute.fsd(Y,X)
# However, if true and imputed values are constant but different,
# FSD is not calculable. An error is displayed.
## Not run:
X <- rep(runif(1), 10);Y <- rep(runif(1), 10)
compute.fsd(Y,X)
## End(Not run)
``` |

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