[R] Decompose an irregular daily time series with missing values

[Dag J. Steinskog]

Dear all,

I have a daily time series for the months April to September (183 says) for
a 40 years period. It contain missing values. I would like to extract a
seasonal component, trend component and irregular component using an
adaptive model. 

#Commands for making a time series: 
timeser<-rnorm(183*40)
#Add some missing values:
timeser[c(5,77,98,100,105,1000,1340,2001,3277,3278,3279,4004:4009,7000)]<-NA

I had a look on the functions decompose and stl. But it seems unsuitable for
my problem. I appreciate if someone can help me out!
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