run_GB_family {binequality} | R Documentation |

## A function to fit a parametric distributions to binned data.

### Description

This function fits a series of parametric distributions from the GB family to binned data.

### Usage

```
run_GB_family(ID,hb,bin_min,bin_max,obs_mean,ID_name,quantiles,modelsToFit,return_params)
```

### Arguments

`ID` |
a (non-empty) object containing the group ID for each row. Importantly, ID, bh, bin_min, bin_max, and obs_mean MUST be the same length and be in the SAME order. |

`hb` |
a (non-empty) object containing the number of observations in each bin. Importantly, ID, bh, bin_min, bin_max, and obs_mean MUST be the same length and be in the SAME order. |

`bin_min` |
a (non-empty) object containing the lower bound of each bin. Currently, this package cannot handle data with open lower bounds. Importantly, ID, bh, bin_min, bin_max, and obs_mean MUST be the same length and be in the SAME order. |

`bin_max` |
a (non-empty) object the upper bound of each bin. Currently, this package can only handle the upper-most bin being open ended. Importantly, ID, bh, bin_min, bin_max, and obs_mean MUST be the same length and be in the SAME order. |

`obs_mean` |
a (non-empty) object containing the mean for each group. Importantly, ID, bh, bin_min, bin_max, and obs_mean MUST be the same length and be in the SAME order. |

`ID_name` |
a (non-empty) object containing column name for the ID column. |

`quantiles` |
a (non-empty) vector of quantiles for use in calculating metrics. The default is seq(0.006,0.996, length.out = 1000). |

`modelsToFit` |
a (non-empty) vector of model names as characters, currently limited to the following distributions GB2, GG, BETA2, DAGUM, SINGMAD, LOGNO, WEI, GA, LOGLOG, PARETO2. |

`return_params` |
a (non-empty) logical indicating whether to retunr the parameters. The default is TRUE. |

### Details

Fits a GAMLSS and estimates a number of metrics, see value.

### Value

returns a list with "fit" = fitted model and metrics, "fit.filter" = filtered for undefined moments fitted model and metrics, "best_model" = best model results, "best_model.filter" = filtered for undefined moments best model results.

### See Also

### Examples

```
data(state_bins)
use_states <- which(state_bins[,'State'] == 'Texas')
TX <- state_bins[use_states,]
LNO_WEI_GA <- run_GB_family(ID = TX[,'State'], hb = TX[,'hb'],
bin_min = TX[,'bin_min'], bin_max = TX[,'bin_max'], obs_mean =
rep(NA, length(use_states)), ID_name = "State", quantiles =
seq(0.006,0.996, length.out = 1000), modelsToFit =
c('LOGNO','WEI','GA'))
```

*binequality*version 1.0.4 Index]