impRZalr | R Documentation |

A modified EM alr-algorithm for replacing rounded zeros in compositional data sets.

```
impRZalr(
x,
pos = ncol(x),
dl = rep(0.05, ncol(x) - 1),
eps = 1e-04,
maxit = 50,
bruteforce = FALSE,
method = "lm",
step = FALSE,
nComp = "boot",
R = 10,
verbose = FALSE
)
```

`x` |
compositional data |

`pos` |
position of the rationing variable for alr transformation |

`dl` |
detection limit for each part |

`eps` |
convergence criteria |

`maxit` |
maximum number of iterations |

`bruteforce` |
if TRUE, imputations over dl are set to dl. If FALSE, truncated (Tobit) regression is applied. |

`method` |
either “lm” (default) or “MM” |

`step` |
if TRUE, a stepwise (AIC) procedure is applied when fitting models |

`nComp` |
if determined, it fixes the number of pls components. If “boot”, the number of pls components are estimated using a bootstraped cross validation approach. |

`R` |
number of bootstrap samples for the determination of pls components. Only important for method “pls”. |

`verbose` |
additional print output during calculations. |

Statistical analysis of compositional data including zeros runs into problems, because log-ratios cannot be applied. Usually, rounded zeros are considerer as missing not at random missing values. The algorithm first applies an additive log-ratio transformation to the compositions. Then the rounded zeros are imputed using a modified EM algorithm.

`xOrig ` |
Original data frame or matrix |

`xImp ` |
Imputed data |

`wind ` |
Index of the missing values in the data |

```
iter
``` |
Number of iterations |

`eps ` |
eps |

Matthias Templ and Karel Hron

Palarea-Albaladejo, J., Martin-Fernandez, J.A. Gomez-Garcia, J. (2007)
A parametric approach for dealing with compositional rounded zeros.
*Mathematical Geology*, 39(7), 625-645.

`impRZilr`

```
data(arcticLake)
x <- arcticLake
## generate rounded zeros artificially:
x[x[,1] < 5, 1] <- 0
x[x[,2] < 47, 2] <- 0
xia <- impRZalr(x, pos=3, dl=c(5,47), eps=0.05)
xia$xImp
```

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