RankNorm | R Documentation |

Applies the rank-based inverse normal transform (INT) to a numeric vector. The INT can be broken down into a two-step procedure. In the first, the observations are transformed onto the probability scale using the empirical cumulative distribution function (ECDF). In the second, the observations are transformed onto the real line, as Z-scores, using the probit function.

```
RankNorm(u, k = 0.375, ties.method = "average")
```

`u` |
Numeric vector. |

`k` |
Offset. Defaults to (3/8), corresponding to the Blom transform. |

`ties.method` |
Method of breaking ties, passed to |

Numeric vector of rank normalized values.

Direct INT test

`DINT`

.Indirect INT test

`IINT`

.Omnibus INT test

`OINT`

.

```
# Draw from chi-1 distribution
y <- stats::rchisq(n = 1e3, df = 1)
# Rank normalize
z <- RankNorm(y)
# Plot density of transformed measurement
plot(stats::density(z))
```

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.