I have data on temperature from 1969 to 2013 (link).
I want to predict next year's temperature using an ARIMA model with finding correlation between predicted value and actual value. So I want to use data from 1969 to 2010 and then I want to predict for next 3 years. Furthermore, I want to compare it with the actual value and plot the graph and find accuracy.
But just to predict I gave all input from 1969 to 2013. I want to predict for the next year. As by seeing the ACF and PACF, I found that one difference is sufficient. My code is like this:
read <- read.csv('G:/URMAY_CODE/day_temp_file.csv') read_1 <- ts(read[,2], start=c(1969,1), frequency=365.25) ARIMA_FIT <- auto.arima(read_1, d=1, approximation=T, trace=T) ## Best model: ARIMA(3,1,1) summary(ARIMA_FIT) acf(residuals(ARIMA_FIT)) ## I have plot ACF of the residuals form the arima(3,1,1) ## plot(forecast(ARIMA_FIT), xlab="temperature", ylab="years") ## this shows me forecast like this
I want something like zig-zag like but it is not giving that. I searched all the way through internet they are directly plotting the graph like this, but they are getting a zig-zag graph.
Sub Question: What is the role of
auto.arima(), and how it is applicable to my code?
(I need help with the plotting as well as the comparison.)