Description Usage Arguments Value Author(s)
Takes a longitudinal dataset and impute missing value with a machine learning-based method.
1 2 |
data |
A dataset (more than two longitudinal mesurements) |
d |
Percentage of change between two-sided mesurements to consider it bigger, smaller or the same, It useful to built the var.matrix. |
method |
It represent the type of machine learning algorithm. 'k' for k-mean and 'h' for hierical. |
cluster |
It's the number of cluster. Default setting it's 6. It depends on number of longitudinal mesurements. It could be use mvls.print to decide best cluster number. |
nstart |
It is the nstart setting of function k-mean. Defualt it'20. Not requested for 'h' method. |
pre.imp |
TRUE/FALSE (default F). It permit to pre-impute data to built the vari.matrix, It could be reduce cluster with only missing value. |
imp.method |
It's the type of pre-imputation. Defaul it's 'mean', but there is also 'locf' possibility. |
$data It's the data-set with imputation.
$cluster It's the cluster matrix.
$matrix It's the vari.matrix.
$sd.1 It contains the sd for each data imputed at single imputation method. Different from sd.2.
$vari.matrix It's the variation matrix
$data.norm It's the imputation dataset normalized
Lorenzo Querci <lorenzo.querci@studio.unibo.it>
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