nmad_test {distributionsrd} | R Documentation |

## Normalized Absolute Deviation

### Description

Calculates the Normalized Absolute Deviation between the empirical moments and the moments of the provided distribution. Corresponds to the Kolmogorov-Smirnov test statistic for the zeroth moment.

### Usage

```
nmad_test(
x,
r = 0,
dist,
prior = 1,
coeff,
stat = c("NULL", "max", "sum"),
...
)
```

### Arguments

`x` |
data vector |

`r` |
moment parameter |

`dist` |
character vector containing distribution |

`prior` |
named list of priors, defaults to 1 |

`coeff` |
named list of coefficients |

`stat` |
character vector indicating which statistic should be calculated: none (NULL), the maximum deviation "max" or the sum of deviations "sum". Defaults to NULL. |

`...` |
Additional arguments can be passed to the parametric moment call. |

### Examples

```
x <- rlnorm(1e2, meanlog = -0.5, sdlog = 0.5)
nmad_test(x = x, r = 0, dist = "lnorm", coeff = c(meanlog = -0.5, sdlog = 0.5))
nmad_test(x = x, r = 0, dist = "lnorm", coeff = c(meanlog = -0.5, sdlog = 0.5), stat = "max")
nmad_test(x = x, r = 0, dist = "lnorm", coeff = c(meanlog = -0.5, sdlog = 0.5), stat = "sum")
```

[Package

*distributionsrd*version 0.0.6 Index]