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

Computes the geometric mean.

1 2 3 4 5 6 7 |

`x` |
a numeric vector or matrix of data |

`...` |
further arguments to compute the mean |

The geometric mean is defined as:

*
geometricmean(x) := \code{prod(x)^(1/length(x))}
*

The geometric mean is actually computed by
`exp(mean(log(c(unclass(x))),...))`

.

The geometric means of x as a whole (geometricmean), its rows (geometricmeanRow) or its columns (geometricmeanCol).

The the first three functions take the geometric mean of all non-missing values. This is because they should yield a result in term of data analysis.

Contrarily, the gsi.* functions inherit the arithmetic IEEE policy of R through
`exp(mean(log(c(unclass(x))),...))`

. Thus, NA codes a not available i.e.
not measured, NaN codes a below detection limit, and 0.0 codes a structural zero.
If any of the elements involved is 0, NA or NaN the result is of the same
type. Here 0 takes precedence over NA, and NA takes precedence
over NaN. For example, if a structural 0 appears, the geometric mean is 0
regardless of the presence of NaN's or NA's in the rest. Values below detection
limit become NaN's if they are coded as negative values.

K.Gerald v.d. Boogaart http://www.stat.boogaart.de

1 2 3 4 5 6 | ```
geometricmean(1:10)
geometricmean(c(1,0,NA,NaN)) # 0
X <- matrix(c(1,NA,NaN,0,1,2,3,4),nrow=4)
X
geometricmeanRow(X)
geometricmeanCol(X)
``` |

```
Loading required package: tensorA
Attaching package: 'tensorA'
The following object is masked from 'package:base':
norm
Loading required package: robustbase
Loading required package: energy
Loading required package: bayesm
Welcome to compositions, a package for compositional data analysis.
Find an intro with "? compositions"
Attaching package: 'compositions'
The following objects are masked from 'package:stats':
cor, cov, dist, var
The following objects are masked from 'package:base':
%*%, scale, scale.default
[1] 4.528729
[1] 0
[,1] [,2]
[1,] 1 1
[2,] NA 2
[3,] NaN 3
[4,] 0 4
[1] 1 2 3 0
[1] 0.000000 2.213364
```

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