ci_mean_min {Compind} | R Documentation |

## Mean-Min Function

### Description

The Mean-Min Function (MMF) is an intermediate case between arithmetic `mean`

, according to which no unbalance is penalized, and `min`

function, according to which the penalization is maximum. It depends on two parameters that are respectively related to the intensity of penalization of unbalance (`\alpha`

) and intensity of complementarity (`\beta`

) among indicators.

### Usage

`ci_mean_min(x, indic_col, alpha, beta)`

### Arguments

`x` |
A data.frame containing simple indicators. |

`indic_col` |
Simple indicators column number. |

`alpha` |
The intensity of penalisation of unbalance among indicators, |

`beta` |
The intensity of complementarity among indicators, |

### Value

An object of class "CI". This is a list containing the following elements:

`ci_mean_min_est` |
Composite indicator estimated values. |

`ci_method` |
Method used; for this function ci_method="mean_min". |

### Author(s)

Vidoli F.

### References

Casadio Tarabusi, E., & Guarini, G. (2013) "*An unbalance adjustment method
for development indicators*", Social indicators research, 112(1), 19-45.

### See Also

### Examples

```
data(EU_NUTS1)
data_norm = normalise_ci(EU_NUTS1,c(2:3),c("NEG","POS"),method=2)
CI = ci_mean_min(data_norm$ci_norm, alpha=0.5, beta=1)
```

*Compind*version 3.1 Index]