imputeROS {BLOQ} | R Documentation |
function to impute BLOQ's with regression on order statistics (ROS) approach.
imputeROS(inputData, LOQ, isMultiplicative = FALSE, useSeed = runif(1))
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) |
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)
Vahid Nassiri, Helen Yvette Barnett
# 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)