impnorm: Impute missing multivariate normal data
In rrcovNA: Scalable Robust Estimators with High Breakdown Point for Incomplete Data
impNorm R Documentation
Impute missing multivariate normal data
Description
Draws missing elements of a data matrix under the multivariate normal
model and a user-supplied parameter
Usage
impNorm(x)
Arguments
x
the original incomplete data matrix.
Details
This function simply uses imp.norm from package norm.
Value
a matrix of the same form as x, but with all missing values filled in
with simulated values drawn from their predictive distribution given
the observed data and the specified parameter.
References
See Section 5.4.1 of Schafer (1996).
See Also
prelim.norm, makeparam.norm, and rngseed.
Examples
data(bush10)
impNorm(bush10) #impute missing data under the MLE
rrcovNA documentation built on July 9, 2023, 6:26 p.m.
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.
| impNorm | R Documentation |
Impute missing multivariate normal data
Description
Draws missing elements of a data matrix under the multivariate normal model and a user-supplied parameter
Usage
impNorm(x)
Arguments
x |
the original incomplete data matrix. |
Details
This function simply uses imp.norm from package norm.
Value
a matrix of the same form as x, but with all missing values filled in
with simulated values drawn from their predictive distribution given
the observed data and the specified parameter.
References
See Section 5.4.1 of Schafer (1996).
See Also
prelim.norm, makeparam.norm, and rngseed.
Examples
data(bush10)
impNorm(bush10) #impute missing data under the MLE
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.