imputeROS {BLOQ} | R Documentation |

## imputing BLOQ's using regression on order statistics

### Description

function to impute BLOQ's with regression on order statistics (ROS) approach.

### Usage

```
imputeROS(inputData, LOQ, isMultiplicative = FALSE, useSeed = runif(1))
```

### Arguments

`inputData` |
numeric matrix or data frame of the size n by J (n the sample size and J the number of time points) the input dataset |

`LOQ` |
scalar limit of quantification value |

`isMultiplicative` |
logical variable indicating whether an additive error model (FALSE) or a multiplicative model (TRUE) should be used |

`useSeed` |
scalar, set a seed to make the results reproducible, default is runif(1), it is used to randomly order the first imputed column (if the first column has any BLOQ's) |

### Value

the imputed dataset: a numeric matrix or data frame of the size n by J (n the sample size and J the number of time points)

### Author(s)

Vahid Nassiri, Helen Yvette Barnett

### Examples

```
# generate data from Beal model with only fixed effects
set.seed(111)
genDataFixedEffects <- simulateBealModelFixedEffects(10, 0.693,
+ 1, 1, seq(0.5,3,0.5))
imputeROS(genDataFixedEffects, 0.1)
```

[Package

*BLOQ*version 0.1-1 Index]