Description Usage Arguments Value Note Examples
Standardize the given data matrix per column, over the rows, with multiple imputation for missing data.
1 | pre_process(DATA, weight)
|
DATA |
A data matrix |
weight |
Whether the data matrix is weighted. |
a standardized matrix
Weighting a data matrix (i.e., weight = TRUE
) is performed as follows. Each cell in the data is devided by the sqaure root of the number of variables.
More details regarding data pre-processing, please see:
Van Deun, K., Smilde, A.K., van der Werf, M.J., Kiers, H.A.L., & Mechelen, I.V. (2009). A structured overview of simultaneous component based data integration. BMC Bioinformatics, 10:246.
The missing values are handled by means of Multivariate Imputation by Chained Equations (MICE). The number of multiple imputation is 5. More details see:
Buuren, S. V., & Groothuis-Oudshoorn, K. (2010). mice: Multivariate imputation by chained equations in R. Journal of statistical software, 1-68.
1 2 3 4 | ## Not run:
pre_process(matrix(1:12, nrow = 3, ncol = 4))
## End(Not run)
|
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