[R] how to predict/forecast missing values in time series ?

[Jeff Newmiller]

library (zoo)
?na.approx

Note that you need to define an index (time base) to go along with your data, but that could be as simple as a sequence of integers.
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sagarnikam123 <sagarnikam123 at gmail.com> wrote:

>i have time series as
>1.3578511
>0.5119648
>1.3189847
>0.9214787
>1.2272616
>4.9167998
>1.2272616
>1.2272616
>0.8854192
>2.3386331
>1.6132899
>0.2030302
>0.8426226
>1.2277843
>NA
>1.3189847
>1.3578511
>0.8530141
>2.3386331
>1.0541099
>0.7747481
>0.5764672
>1.3189847
>1.2160533
>1.2272616
>0.6715839
>0.9651803
>1.6132899
>1.2006974
>0.6875047
>1.3245534
>1.2006974
>0.8221709
>1.3101684
>1.6132899
>1.6132899
>1.2006974
>1.3189847
>1.0018480
>1.2277843
>1.4424190
>1.6132899
>1.2277843
>1.2006974
>0.7779642
>0.9381081
>0.8854192
>NA
>NA
>1.3189847
>1.1070461
>0.8221709
>4.9167998
>0.9214787
>1.3189847
>1.3189847
>1.2277843
>1.4424190
>1.6132899
>1.6132899
>4.9167998
>0.8235792
>0.9708839
>1.1070461
>1.2160533
>0.8354292
>1.4424190
>1.1958634
>0.5119648
>1.4424190
>1.4424190
>1.6132899
>1.6132899
>0.6710844
>1.2272616
>0.9708839
>0.8890464
>1.4424190
>0.8890464
>0.8221709
>1.1958634
>0.8132233
>0.4630722
>4.9167998
>0.8890464
>1.3189847
>0.7373181
>1.1070461
>1.2279813
>0.8890464
>0.3588158
>1.4424190
>0.8132233
>0.4297043
>1.3578511
>4.9167998
>1.2272616
>0.8426226
>1.4424190
>1.6132899
>NA
> 
>
>in which NA are missing values,i want to predict/forecast it,i search
>on
>internet,i found that Amelia packages can impute missing values;
>i used but it giving error,how can i resolve it
>
>library(Amelia)
>t<-read.table("C:\\Users\\exam\\Desktop\\missing_ts.txt")
>
>> a.out <- amelia(t)
>Amelia Error Code:  42 
>There is only 1 column of data. Cannot impute
> 
>> amelia(x=as.matrix(1:101,t$V1))
>Amelia Error Code:  39 
>Your data has no missing values.  Make sure the code for 
>missing data is set to the code for R, which is NA
>
>> amelia(t$V1)
>Error in colSums(!is.na(x)) : 
>  'x' must be an array of at least two dimensions
>
>is my way of predicting wrong?,if yes,then which method should i
>follow?
> 
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>--
>View this message in context:
>http://r.789695.n4.nabble.com/how-to-predict-forecast-missing-values-in-time-series-tp4630588.html
>Sent from the R help mailing list archive at Nabble.com.
>
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