R Forecasting Package and Daily Timeseries

Question

I have been using the Forecast Package in R but have found it difficult to load my own daily time series into a ts object and then use this with the forecasting algorithms. I have instead used zoo to create my daily timeseries object, but I can not pass this directly to forecasting algorithms in the R Forecast package.

Any help in the correct direction would be much appreciated. I feel very stuck with this.

Thanks

Hi Here is some sample code. With a simple quarterly dataset, I can get some prediction working but with a daily dataset I can't get it working. Many Thanks

require("forecast")
require("fpp")

# Example from Forecasting Principles and Practice
# http://otexts.com/fpp/2/5/

#beer2 <- window(ausbeer,start=1992,end=2006-.1)

#start with a really small dataset (only 6 data points)
beer2 <- window(ausbeer,start=2006,end=2006-.1)
print(beer2)

beerfit1 <- meanf(beer2,h=11)
beerfit2 <- rwf(beer2,h=11)
beerfit3 <- snaive(beer2,h=11)

plot(beerfit1, plot.conf=FALSE, main="Forecasts for quarterly beer production")
lines(beerfit2$mean,col=2)
lines(beerfit3$mean,col=3)
lines(ausbeer)
legend("topright", lty=1, col=c(4,2,3), legend=c("Mean method","Naive method","Seasonal     naive method"))

beer3 <- window(ausbeer, start=2006)
accuracy(beerfit1, beer3)
accuracy(beerfit2, beer3)
accuracy(beerfit3, beer3)

#now make a really small daily dataset (Each day for two weeks)
forecast_datesequence = seq(from=as.Date("2013-05-06"), to=as.Date("2013-05-19"), by=1)
vals <- c(100,150,300,150,100,45,25,100,150,300,150,100,45,25)

dailyzoo_ts <- zoo(vals, forecast_datesequence)
print(daily_ts)

dailyfit1 <- meanf(coredata(dailyzoo_ts),h=7)
dailyfit2 <- rwf(coredata(dailyzoo_ts),h=7)
dailyfit3 <- snaive(coredata(dailyzoo_ts),h=7)

plot(dailyfit1, plot.conf=FALSE, main="Daily Data Over 2 Week Period")
lines(dailyfit2$mean,col=2)
lines(dailyfit3$mean,col=3)
lines(dailyzoo_ts)
legend("topright", lty=1, col=c(4,2,3), legend=c("Mean method","Naive method","Seasonal naive method"))

Here is an updated bit of R code that still does not work

#now make a really small daily dataset (Each day for two weeks)
forecast_datesequence = seq(from=as.Date("2013-05-06"), to=as.Date("2013-05-19"), by=1)
vals <- c(100,150,300,150,100,45,25,100,150,300,150,100,45,25)

dailyzoo_ts <- zoo(vals, forecast_datesequence)
print(daily_ts)

z <- zoo(coredata(dailyzoo_ts), 1:14/7)
print(z)
plot(forecast(z))
#stl(z)

dailyfit1 <- meanf(z,h=7)
dailyfit2 <- rwf(z,h=7)
dailyfit3 <- snaive(z,h=7)

plot(dailyfit1, plot.conf=FALSE, main="Daily Data Over 2 Week Period")
lines(dailyfit2$mean,col=2)
lines(dailyfit3$mean,col=3)
lines(z)
legend("topright", lty=1, col=c(4,2,3), legend=c("Mean method","Naive method","Seasonal naive method"))

Many Thanks

R Forecasting Package and Daily Timeseries

Answers (1)

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