时间序列每日数据建模

Question

I am looking to forecast my time series. I have the following period daily data 2021-Jan-1 to 2022-Jul-1. So I have a column of observations for each day. what I tried so far:

d1=zoo(data, seq(from = as.Date("2021-01-01"), to = as.Date("2022-07-01"), by = 1))
tsdata <- ts(d1, frequency = 365)
ddata <- decompose(tsdata, "multiplicative")

I get following error here:

Error in decompose(tsdata, "multiplicative") : time series has no or less than 2 periods

From what i have read it seems like because I do not have two full years? is that correct? I have tried doing it weekly as well:

series <- ts(data, frequency = 52, start = c(2021, 1))  

• getting the same issue.

How do I go about it without having to extend my dataset to two years since I do not have that, and still being able to decompose it? Plus when I am actually trying to forecast it, it isn't giving me good enough forecast: Plot with forecast

My data somewhat resembles a bell curve during that period. so is there a better fitting timeseries model I can apply instead?

Answer 1

A weekly frequency for daily data should have frequency = 7 , not 52 . It's possible that this fix to your code will produce a model with a seasonal term.

I don't think you'll be able to produce a time series model with annual seasonality with less than 2 years of data.

You can either produce a model with only weekly seasonality (I expect this is what most folks would recommend), or if you truly believe in the annual seasonal pattern exhibited in your data, your "forecast" can be a seasonal naive forecast that is simply last year's value for that particular day. I wouldn't recommend this, because it just seems risky, and I don't really see the same trajectory in your screenshot over 2022 that's apparent in 2021.

Answer 2

decompose requires two full cycles and that a full cycle represent 1 time unit. ts class can't use Date class anyways. To use frequency 7 we must use times 1/7th apart such as 1, 1+1/7, 1+2/7, etc. so that 1 cycle (7 days) covers 1 unit. Then just label the plot appropriately rather than using those times on the X axis. In the code below use %Y in place of %y if the years start in 19?? and end in 20?? so that tapply maintains the order.

# test data
set.seed(123)
s <- seq(from = as.Date("2021-01-01"), to = as.Date("2022-07-01"), by = 1)
data <- rnorm(length(s))
tsdata <- ts(data, freq = 7)

ddata <- decompose(tsdata, "multiplicative")

plot(ddata, xaxt = "n")
m <- tapply(time(tsdata), format(s, "%y/%m"), head, 1)
axis(1, m, names(m))