Using geom_gls

library(ecodata)

Using geom_gls()

Also included in this package is a “geom” extension of ggplot2 for assessing trends in time series. This function fits four trend models to each series, uses AICc to select the best model fit, and then implements a likelihood-ratio test to determine if a trend is present. If a significant trend is present (P < 0.05), then the trend line is plotted with the series. By default, a purple line color is assigned to negative trends and orange to positive trends. More detailed information about this method is available here.

geom_gls() follows the same rules as other ggplot stats/geoms. For example,

m <- 0.1
x <- 1:30
y <-  m*x + rnorm(30, sd = 0.35)

data <- data.frame(x = x,
                  y = y)

#Plot series with trend 
ggplot2::ggplot(data = data,aes(x = x, y = y)) +
  geom_line() +
  geom_gls()

produces