Description Usage Arguments Details Author(s) Examples

Calculate the FA2 between two univariate signals Y (imputed values) and X (true values).

1 | ```
compute.fa2(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 FA2 value which corresponds to the percentage of pairs of values (*x_{i}, y_{i}*) satisfying the condition *0,5 <= (y_{i}/x_{i}) <= 2*.
FA2 is close to 1, the imputation model is more accurate.
Both vectors Y and X must be of equal length, on the contrary an error will be displayed.
In both input vectors, eventual 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 | ```
data(dataFSMUMI)
X <- dataFSMUMI[, 1] ; Y <- dataFSMUMI[, 2]
compute.fa2(Y,X)
compute.fa2(Y,X, verbose = TRUE)
# By definition, if pairs of true and imputed values are zero,
# FA2 corresponding to this pair of values equals 1.
X[1] <- 0
Y[1] <- 0
compute.fa2(Y,X)
``` |

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