One line per learner across the grains, at the across-variable mean of the per-variable score, with a 95 percent interval from its standard error across variables, on Student's t with one degree of freedom fewer than there are variables. An open circle marks each learner's best grain, which is where the curve says the record stops paying for being read more finely.
Usage
# S3 method for class 'timesift_ladder'
plot(x, col = NULL, interval = TRUE, ...)Arguments
- x
A
grain_ladder()result.- col
One colour per learner, recycled.
- interval
Draw the interval across variables.
- ...
Passed to
graphics::plot().
Examples
set.seed(1)
t <- seq(as.POSIXct("2021-09-01", tz = "UTC"), by = "hour", length.out = 24 * 200)
units <- sprintf("p%02d", 1:60)
warmth <- rnorm(60)
d <- data.frame(
plot = rep(units, each = length(t)), t = rep(t, length(units)),
temp = as.numeric(vapply(warmth, function(w) w + sin(seq_along(t) / 300) + rnorm(length(t)),
numeric(length(t)))))
y <- matrix(rbinom(120, 1, plogis(c(warmth, -warmth))), nrow = 60,
dimnames = list(units, c("sp1", "sp2")))
x <- grain_matrix(d, plot, t, temp, grain = c("day", "week", "month"))
lad <- grain_ladder(x, y, elasticnet(), folds = fold_map(y, v = 3), verbose = FALSE)
plot(lad)