Estimate the missing entries in a response data

Usage

estimate_missing_value(data, nodor, method = "PC")

Arguments

data: a data frame or matrix, contaning the consensus response values
nodor: a numeric value, specifying the number of the selected odors
method: character string, specifying the method ("PC" (Pearson's coefficient) and "Knn" (k nearest neighbors)) for estimation, the default is "PC".

Details

A wrapper programe for using Pearson Correlation or k-nearest neighbors to estimate the missing entries in a response matrix.

References

Kim, H., Golub, G. H. & Park, H., Missing value estimation for DNA microarray gene expression data: local least squares imputation., 2005, Bioinformatics, 21, 187-198

Author

Shouwen Ma <shouwen.ma@uni-konstanz.de>

Examples

if (FALSE) { # \dontrun{
# load data
library(DoOR.data)
data(door_response_matrix)

# pick an example subset
subset <- door_response_matrix[1:100, 11:30]

# estimate missing values
est.data <- estimate_missing_value(data = subset, nodor = 6)
} # }