Description Usage Arguments Examples
summarize the autocorrelation in
1 | acf.summary(data, variables, order.by = NULL, lag.max = 100)
|
data |
data.table containing variables named in 'variables' and 'order.by' |
variables |
character vector listing columns of 'data' to be explored for autocorrelation |
order.by |
optionally, order 'data' by variables in character vector 'order.by' |
lag.max |
maximum block size to explore (default=100) |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | ## simulate data with 10 repeated observations in a row - ie there
## should be autocorrelation only within windows <= 10
library(data.table)
data <- genomic.autocorr:::.sim.data()
summ <- acf.summary(data,c("x","y0","y1"),lag.max=20)
## plot it
df <- melt(summ,c("lag","variable"),variable.name="acf")
par(mfrow=c(2,1))
matplot(matrix(df[acf=="full",]$value,ncol=3),
main="full",
pch=c("x","o","+"),
type="b")
abline(h=0,lty=2)
legend("bottomright",
c("x","y0","y1"),
pch = "xo+", col = 1:3)
matplot(matrix(df[acf=="partial",]$value,ncol=3),
main="partial",
pch=c("x","o","+"),
type="b")
abline(h=0,lty=2)
legend("bottomright",
c("x","y0","y1"),
pch = "xo+", col = 1:3)
|
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