missar: Generate Data that is Missing At Random (MAR)
In misspi: Missing Value Imputation in Parallel
missar R Documentation
Generate Data that is Missing At Random (MAR)
Description
Simulates missing value at random as NA for a given matrix.
Usage
missar(x, miss.rate = 0.2, miss.var = 1)
Arguments
x
a matrix to be used to fill in missing values as NA.
miss.rate
a value of missing rate within the range (0, 1) for variables that contain missing values.
miss.var
proportion of variables (columns) that contain missing values.
Value
x a matrix with missing values in "NA".
Author(s)
Zhongli Jiang jiang548@purdue.edu
See Also
misspi
Examples
set.seed(0)
data(toxicity, package = "misspi")
toxicity.miss <- missar(toxicity, 0.4, 1)
toxicity.miss[1:5, 1:5]
misspi documentation built on Oct. 17, 2023, 5:13 p.m.
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| missar | R Documentation |
Generate Data that is Missing At Random (MAR)
Description
Simulates missing value at random as NA for a given matrix.
Usage
missar(x, miss.rate = 0.2, miss.var = 1)
Arguments
x |
a matrix to be used to fill in missing values as NA. |
miss.rate |
a value of missing rate within the range (0, 1) for variables that contain missing values. |
miss.var |
proportion of variables (columns) that contain missing values. |
Value
x a matrix with missing values in "NA".
Author(s)
Zhongli Jiang jiang548@purdue.edu
See Also
misspi
Examples
set.seed(0)
data(toxicity, package = "misspi")
toxicity.miss <- missar(toxicity, 0.4, 1)
toxicity.miss[1:5, 1:5]
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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