My time-series data includes date-time and temperature columns as follows:
rn25_29_o:
ambtemp dt
1 -1.96 2007-09-28 23:55:00
2 -2.02 2007-09-28 23:57:00
3 -1.92 2007-09-28 23:59:00
4 -1.64 2007-09-29 00:01:00
5 -1.76 2007-09-29 00:03:00
6 -1.83 2007-09-29 00:05:00
I am using median smoothing function to enhance small fluctuations that are caused because of imprecise measurements.
unique_timeStamp <- make.time.unique(rn25_29_o$dt)
temp.zoo<-zoo(rn25_29_o$ambtemp,unique_timeStamp)
m.av<-rollmedian(temp.zoo, n,fill = list(NA, NULL, NA))
subsequently, the output of the median smoothing is used for building temporal model and achieving predictions by using the following code:
te = (x.fit = arima(m.av, order = c(1, 0, 0)))
# fit the model and print the results
x.fore = predict(te, n.ahead=50)
Finally, I encounter with the following error:
Error in seq.default(head(tt, 1), tail(tt, 1), deltat) : 'by' argument is much too small
FYI: The modeling and prediction function works properly by using original time-series data.
Please, guide me through this error.
The problem occurred because of the properties of the zoo package.
Thus, the code can be amended to :
Median_ambtemp <- rollmedian(ambtemp,n,fill = list(NA, NULL, NA)) te = (x.fit = arima(Median_ambtemp, order = c(1, 0, 0)))
# fit the model and print the results
x.fore = predict(te, n.ahead=5)