estimate_missing_value: Estimate the missing entries in a response data

In ropensci/DoOR.functions: Integrating Heterogeneous Odorant Response Data into a Common Response Model: A DoOR to the Complete Olfactome

Estimate the missing entries in a response data

Description

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.

Author(s)

Shouwen Ma <[e-mail]>

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

Examples

## Not run: 
# 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)

## End(Not run)

ropensci/DoOR.functions documentation built on Feb. 22, 2024, 9:44 a.m.