mice.impute.norm.predict {mice} | R Documentation |
Imputes univariate missing data using the predicted value from a linear regression
mice.impute.norm.predict(y, ry, x, ridge=0.00001, ...)
y |
Incomplete data vector of length |
ry |
Vector of missing data pattern ( |
x |
Matrix ( |
ridge |
Ridge parameter |
... |
Other named arguments. |
Calculates regression
weights from the observed data and and return predicted values to as imputations. The ridge
parameter adds
a penalty term ridge*diag(xtx)
to the variance-covariance matrix xtx
.
A vector of length nmis
with imputations.
Stef van Buuren, 2011
Van Buuren, S., Groothuis-Oudshoorn, K. (2011).
mice
: Multivariate Imputation by Chained Equations in R
.
Journal of Statistical Software, 45(3), 1-67.
http://www.jstatsoft.org/v45/i03/