Tim,
Given you have so little data - I would try
a) prefilter and forecast
Fit a fairly simple ARIMA(0,1,1) model to A and treat 8987 as an outlier -
then predict the fitted series AF with the 3 missing points as forecasts.
Fit another ARIMA(0,1,1) with 7688 as an outlier - then back cast to fill
in past values and use the fitted series BF.
The fitted series AF and BF series are the filtered estimates
Then
b)
Regress BF on AF at time t, i.e use
BF_t = alpha * AF_t + Intercept + error_t
then predict BF_hat = alpha1_hat * AF + Intercept.
Regress AF on BF at time t, i.e use
then predict AF_hat = alpha2_hat * BF + Intercept.
And use these predictions as my (first approx) to the missing values.
Hope this helps!
Gerard
Tim Michelsen
<timmichelsen at gmx
-topmail.de> To
Sent by: r-help at stat.math.ethz.ch
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Subject
Re: [R] inter-timeseries
13/01/2009 22:22 correlation or corrections
Dear R-Users,
I put a small sample data set and script.
Aim: combine two partly overlapping series to one by prediction.
Problem: only overlapping data points are predicted.
Question: How do I predict data for rows 1-9 and 14-16?
Thanks in advance for your advince,
Tim
### CODE ###
x <- read.csv('Buch1.csv')
x
year A B
1 1960 2 NA
2 1961 3 NA
3 1962 4 NA
4 1963 54 NA
5 1964 3 NA
6 1965 324 NA
7 1966 546 NA
8 1967 455 NA
9 1968 456 NA
10 1969 456 67
11 1970 8987 34
12 1971 78 34
13 1972 65 3
14 1973 NA 123
15 1974 NA 7688
16 1975 NA 324
predict(lm(a~b))
10 11 12 13
2527.198 2394.489 2394.489 2269.824
### DATA ###
year,A,B
1960,2,
1961,3,
1962,4,
1963,54,
1964,3,
1965,324,
1966,546,
1967,455,
1968,456,
1969,456,67
1970,8987,34
1971,78,34
1972,65,3
1973,,123
1974,,7688
1975,,324
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