25

With acf we can make ACF plot in base R graph.

x <- lh acf(x)

enter image description here

The following code can be used to get the ACF plot in ggplot2.

conf.level <- 0.95 ciline <- qnorm((1 - conf.level)/2)/sqrt(length(x)) bacf <- acf(x, plot = FALSE) bacfdf <- with(bacf, data.frame(lag, acf)) library(ggplot2) q <- ggplot(data=bacfdf, mapping=aes(x=lag, y=acf)) + geom_bar(stat = "identity", position = "identity") q

enter image description here

Question

How to get lines rather than bars or how to set the width of bars so that they look like lines? Thanks

Improve this question
3
  • 2
    Note that there's a ggplot2 wrapper for this: github.com/dewittpe/qwraps. Install with devtools::install_github("dewittpe/qwraps"). Commented Sep 26, 2014 at 7:47
  • This is extremely useful post. I'm wondering if creating Stata-like Cross-correlogram for bivariate time series would be achievable with use of the suggested approach? Commented Jan 17, 2016 at 23:36
  • 2
    @konrad try the following code: library(ggfortify) p1 <- autoplot(acf(AirPassengers, plot = FALSE), conf.int.fill = '#0000FF', conf.int.value = 0.8, conf.int.type = 'ma') print(p1) library(cowplot) ggdraw(switch_axis_position(p1, axis = 'xy', keep = 'xy')) Commented Jan 18, 2016 at 15:29

6 Answers 6

Reset to default
30

You're probably better off plotting with line segments via geom_segment()

library(ggplot2) theme_set(theme_bw()) set.seed(123) x <- arima.sim(n = 200, model = list(ar = 0.6)) bacf <- acf(x, plot = FALSE) bacfdf <- with(bacf, data.frame(lag, acf)) ciline <- qnorm((1 - 0.95)/2)/sqrt(length(x)) q <- ggplot(data = bacfdf, mapping = aes(x = lag, y = acf)) + geom_hline(aes(yintercept = 0)) + geom_segment(mapping = aes(xend = lag, yend = 0)) + geom_hline(yintercept = -ciline, linetype = 2, color = 'darkblue') + geom_hline(yintercept = ciline, linetype = 2, color = 'darkblue') q

enter image description here

Improve this answer
Sign up to request clarification or add additional context in comments.

2 Comments

This answer is super old (and still useful). Just to notice that you forgot to add geom_hline(aes(yintercept = ciline), linetype = 3, color = 'darkblue') + geom_hline(aes(yintercept = -ciline), linetype = 3, color = 'darkblue') to mimic the lines in the original base plot
Dashed line: linetype=2
5

How about using geom_errorbar with width=0?

ggplot(data=bacfdf, aes(x=lag, y=acf)) + geom_errorbar(aes(x=lag, ymax=acf, ymin=0), width=0)
Improve this answer

Comments

5

forecast::ggAcf() is another option:

library(ggplot2) library(forecast) ggAcf(wineind,lag.max=24)+ labs(title='wineind')
Improve this answer

Comments

4

@konrad; try the following code:

library(ggfortify) p1 <- autoplot(acf(AirPassengers, plot = FALSE), conf.int.fill = '#0000FF', conf.int.value = 0.8, conf.int.type = 'ma') print(p1) library(cowplot) ggdraw(switch_axis_position(p1, axis = 'xy', keep = 'xy'))

enter image description here

Improve this answer

1 Comment

This code did not produce the figure you have attached, the blue region is rectangular in the code you presented
3

From the forecast package comes a function ggtsdisplay that plots both ACF and PACF with ggplot. x is the residuals from the model fit (fit$residuals).

forecast::ggtsdisplay(x,lag.max=30)
Improve this answer

Comments

3

From your answers, I synthesized a ggplot ACF / PACF plotting method :

 require(zoo) require(tseries) require(ggplot2) require(cowplot) ts= zoo(data[[2]]) # data[[2]] because my time series data was the second column # Plot ACP / ACF with IC # How to compute IC for ACF and PACF : # https://stats.stackexchange.com/questions/211628/how-is-the-confidence-interval-calculated-for-the-acf-function ic_alpha= function(alpha, acf_res){ return(qnorm((1 + (1 - alpha))/2)/sqrt(acf_res$n.used)) } ggplot_acf_pacf= function(res_, lag, label, alpha= 0.05){ df_= with(res_, data.frame(lag, acf)) # IC alpha lim1= ic_alpha(alpha, res_) lim0= -lim1 ggplot(data = df_, mapping = aes(x = lag, y = acf)) + geom_hline(aes(yintercept = 0)) + geom_segment(mapping = aes(xend = lag, yend = 0)) + labs(y= label) + geom_hline(aes(yintercept = lim1), linetype = 2, color = 'blue') + geom_hline(aes(yintercept = lim0), linetype = 2, color = 'blue') } acf_ts= ggplot_acf_pacf(res_= acf(ts, plot= F) , 20 , label= "ACF") pacf_ts= ggplot_acf_pacf(res_= pacf(ts, plot= F) , 20 , label= "PACF") # Concat our plots acf_pacf= plot_grid(acf_ts, pacf_ts, ncol = 2, nrow = 1) acf_pacf

Results:

enter image description here

Improve this answer

Comments

Start asking to get answers

Find the answer to your question by asking.

Ask question

Explore related questions

See similar questions with these tags.