Description Usage Arguments Details Value Author(s) References See Also Examples

Routines classifies codes of missing valuesas numbers in objects of the compositions package.

1 2 3 4 5 | ```
missingSummary(x,..., vlabs = colnames(x),
mc=attr(x,"missingClassifier"),
values=eval(formals(missingType)$values))
missingType(x,..., mc=attr(x,"missingClassifier"),
values=c("NMV", "BDT", "MAR", "MNAR", "SZ", "Err"))
``` |

`x` |
a dataset which might contain missings |

`...` |
additional arguments for mc |

`mc` |
optionally in missingSummary, an alternate routine to be used
instead of |

`vlabs` |
labels for the variables |

`values` |
the names of the different types of missings. |

The function mainly counts the various types of missing values.

`missingType`

returns a character vector/matrix with the same dimension and
dimnames as `x`

giving the type of every value.

`missingSummary`

returns a table giving the number of missings of each
type for each variable.

K. Gerald van den Boogaart

Boogaart, K.G., R. Tolosana-Delgado, M. Bren (2006) Concepts for the
handling of zeros and missings in compositional data, *Proceedings of
IAMG 2006, Liege*

compositions.missing

1 2 3 4 5 | ```
data(SimulatedAmounts)
x <- acomp(sa.lognormals)
xnew <- simulateMissings(x,dl=0.05,MAR=0.05,MNAR=0.05,SZ=0.05)
xnew
missingSummary(xnew)
``` |

compositions documentation built on May 30, 2017, 3:25 a.m.

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