问题
I have an XTS time series object which shows a value on the first of each month (representing an aggregated sum for the whole month) during four years.
When I run the stats::acf() function on it, I get a plot with lag (x axis) units in the hundreds of thousands. How can that be if I only have 48 values in my time series? If it is a time unit, then which one, and how can I change it?
Example code:
library(dplyr)
library(lubridate)
library(xts)
set.seed(100)
test <- data.frame(y = c(rep(2012, 12), rep(2013, 12), rep(2014, 12), rep(2015, 12)),
m = rep(seq(1, 12, 1), 4), d = rep(1, 48), value = runif(48, 0, 100))
test <- test %>%
mutate(date = ymd(paste(y, m, d, sep = "-"))) %>%
select(date, value)
test <- xts(test$value, test$date)
acf(test)
回答1:
From the source code we see that we can calculate the lags like this:
sampleT <- as.integer(nrow(test))
nser <- as.integer(ncol(test))
lag.max <- floor(10 * (log10(sampleT) - log10(nser)))
x.freq <- frequency(test)
lag <- outer(0:lag.max, 1/x.freq)
# [,1]
# [1,] 0
# [2,] 86400
# [3,] 172800
# [4,] 259200
# [5,] 345600
# [6,] 432000
# [7,] 518400
# [8,] 604800
# [9,] 691200
#[10,] 777600
#[11,] 864000
#[12,] 950400
#[13,] 1036800
#[14,] 1123200
#[15,] 1209600
#[16,] 1296000
#[17,] 1382400
The time unit is the reciprocal of the frequency unit. To understand how that value is calculated you need to dive into the source code of frequency.zoo, which does something I find difficult to understand at a first glance.
来源：https://stackoverflow.com/questions/35705001/r-time-series-whats-the-lag-unit-for-autocorrelation-function-acf