arcsinh_x {bestNormalize} | R Documentation |

Perform a arcsinh(x) transformation

arcsinh_x(x, standardize = TRUE, ...) ## S3 method for class 'arcsinh_x' predict(object, newdata = NULL, inverse = FALSE, ...) ## S3 method for class 'arcsinh_x' print(x, ...)

`x` |
A vector to normalize with with x |

`standardize` |
If TRUE, the transformed values are also centered and scaled, such that the transformation attempts a standard normal |

`...` |
additional arguments |

`object` |
an object of class 'arcsinh_x' |

`newdata` |
a vector of data to be (potentially reverse) transformed |

`inverse` |
if TRUE, performs reverse transformation |

`arcsinh_x`

performs an arcsinh transformation in the context of
bestNormalize, such that it creates a transformation that can be estimated
and applied to new data via the `predict`

function.

The function is explicitly: log(x + sqrt(x^2 + 1))

A list of class `arcsinh_x`

with elements

`x.t` |
transformed original data |

`x` |
original data |

`mean` |
mean after transformation but prior to standardization |

`sd` |
sd after transformation but prior to standardization |

`n` |
number of nonmissing observations |

`norm_stat` |
Pearson's P / degrees of freedom |

`standardize` |
was the transformation standardized |

The `predict`

function returns the numeric value of the transformation
performed on new data, and allows for the inverse transformation as well.

x <- rgamma(100, 1, 1) arcsinh_x_obj <- arcsinh_x(x) arcsinh_x_obj p <- predict(arcsinh_x_obj) x2 <- predict(arcsinh_x_obj, newdata = p, inverse = TRUE) all.equal(x2, x)

[Package *bestNormalize* version 1.8.0 Index]