A function for computing the rolling and expanding index of minimums of time-series data.
roll_idxmin(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
index of minimums.
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 index of minimums with complete windows
roll_idxmin(x, width = 5)
# rolling index of minimums with partial windows
roll_idxmin(x, width = 5, min_obs = 1)
# expanding index of minimums with partial windows
roll_idxmin(x, width = n, min_obs = 1)
# expanding index of minimums with partial windows and weights
roll_idxmin(x, width = n, min_obs = 1, weights = weights)
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