exp_x {bestNormalize} | R Documentation |

Perform a exp(x) transformation

exp_x(x, standardize = TRUE, warn = TRUE, ...) ## S3 method for class 'exp_x' predict(object, newdata = NULL, inverse = FALSE, ...) ## S3 method for class 'exp_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 |

`warn` |
Should a warning result from infinite values? |

`...` |
additional arguments |

`object` |
an object of class 'exp_x' |

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

`inverse` |
if TRUE, performs reverse transformation |

`exp_x`

performs a simple exponential 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.

A list of class `exp_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) exp_x_obj <- exp_x(x) exp_x_obj p <- predict(exp_x_obj) x2 <- predict(exp_x_obj, newdata = p, inverse = TRUE) all.equal(x2, x)

[Package *bestNormalize* version 1.8.0 Index]