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A function for computing the rolling and expanding maximums of time-series data.
roll_max(x, width, weights = rep(1, width), min_obs = width,
complete_obs = FALSE, na_restore = FALSE, online = TRUE)An object of the same class and dimension as x with the rolling and expanding
maximums.
vector or matrix. Rows are observations and columns are variables.
integer. Window size.
vector. Weights for each observation within a window.
integer. Minimum number of observations required to have a value within a window,
otherwise result is NA.
logical. If TRUE then rows containing any missing values are removed,
if FALSE then each value is used.
logical. Should missing values be restored?
logical. Process observations using an online algorithm.
n <- 15
x <- rnorm(n)
weights <- 0.9 ^ (n:1)
# rolling maximums with complete windows
roll_max(x, width = 5)
# rolling maximums with partial windows
roll_max(x, width = 5, min_obs = 1)
# expanding maximums with partial windows
roll_max(x, width = n, min_obs = 1)
# expanding maximums with partial windows and weights
roll_max(x, width = n, min_obs = 1, weights = weights)
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