[R] multiple imputation with fit.mult.impute in Hmisc - how to replace NA with imputed value?

[Charlie Brush]

I am doing multiple imputation with Hmisc, and
can't figure out how to replace the NA values with
the imputed values.

Here's a general ourline of the process:

 > set.seed(23)
 > library("mice")
 > library("Hmisc")
 > library("Design")
 > d <- read.table("DailyDataRaw_01.txt",header=T)
 > length(d);length(d[,1])
[1] 43
[1] 2666
Do for this data set, there are 43 columns and 2666 rows

Here is a piece of data.frame d:
 > d[1:20,4:6]
  P01  P02  P03
1  0.1 0.16 0.16
2   NA 0.00 0.00
3   NA 0.60 0.04
4   NA 0.15 0.00
5   NA 0.00 0.00
6  0.7 0.00 0.75
7   NA 0.00 0.00
8   NA 0.00 0.00
9  0.0 0.00 0.00
10 0.0 0.00 0.00
11 0.0 0.00 0.00
12 0.0 0.00 0.00
13 0.0 0.00 0.00
14 0.0 0.00 0.00
15 0.0 0.00 0.03
16  NA 0.00 0.00
17  NA 0.01 0.00
18 0.0 0.00 0.00
19 0.0 0.00 0.00
20 0.0 0.00 0.00

These are daily precipitation values at NCDC stations, and
NA values at station P01 will be filled using multiple
imputation and data from highly correlated stations P02 and P08:

 > f <- aregImpute(~ I(P01) + I(P02) + I(P08), 
n.impute=10,match='closest',data=d)
Iteration 13
 > fmi <- fit.mult.impute( P01 ~ P02 + P08 , ols, f, d)

Variance Inflation Factors Due to Imputation:

Intercept       P02       P08
    1.01      1.39      1.16

Rate of Missing Information:

Intercept       P02       P08
    0.01      0.28      0.14

d.f. for t-distribution for Tests of Single Coefficients:

Intercept       P02       P08
242291.18    116.05    454.95
 > r <- apply(f$imputed$P01,1,mean)
 > r
    2     3     4     5     7     8    16    17   249   250   251
0.002 0.430 0.044 0.002 0.002 0.002 0.002 0.123 0.002 0.002 0.002
  252   253   254   255   256   257   258   259   260   261   262
1.033 0.529 1.264 0.611 0.002 0.513 0.085 0.002 0.705 0.840 0.719
  263   264   265   266   267   268   269   270   271   272   273
1.489 0.532 0.150 0.134 0.002 0.002 0.002 0.002 0.002 0.055 0.135
  274   275   276   277   278   279   280   281   282   283   284
0.009 0.002 0.002 0.002 0.008 0.454 1.676 1.462 0.071 0.002 1.029
  285   286   287   288   289   418   419   420   421   422   700
0.055 0.384 0.947 0.002 0.002 0.008 0.759 0.066 0.009 0.002 0.002

------------------------------------------------------------------
So far, this is working great.
Now, make a copy of d:
 > dnew <- d

And then fill in the NA values in P01 with the values in r

For example:
 > for (i in 1:length(r)){
    dnew$P01[r[i,1]] <- r[i,2]
    }
This doesn't work, because each 'piece' of r is two numbers:
 > r[1]
   2
0.002
 > r[1,1]
Error in r[1, 1] : incorrect number of dimensions

My question: how can I separate the the two items in (for example)
r[1] to use the first part as an index and the second as a value,
and then use them to replace the NA values with the imputed values?

Or is there a better way to replace the NA values with the imputed values?

Thanks in advance for any help.