imp.norm {norm} | R Documentation |
Draws missing elements of a data matrix under the multivariate normal model and a user-supplied parameter
imp.norm(s, theta, x)
s |
summary list of an incomplete normal data matrix x created by the
function prelim.norm .
|
theta |
value of the normal parameter under which the missing data are to be
randomly imputed. This is a parameter vector in packed storage, such
as one created by em.norm or da.norm .
|
x |
the original data matrix used to create the summary list s . If this
argument is not supplied, then the data matrix returned by this
function may disagree slightly with the observed values in x due to
rounding errors.
|
This function simply performs one I-step of data augmentation.
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.
Before this function may be used, the random number generator seed
must be initialized with rngseed
at least once in the current S
session.
See Section 5.4.1 of Schafer (1996).
prelim.norm
, makeparam.norm
, and rngseed
.
data(mdata) s_prelim.norm(mdata) #do preliminary manipulations thetahat_em.norm(s) #find the mle rngseed(1234567) #set random number generator seed ximp_imp.norm(s,thetahat,mdata) #impute missing data under the MLE