[R] inter-timeseries correlation or corrections

[Gerard M. Keogh]

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                                             
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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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