moutlier_chisq: Chi-squared test for multivariate outliers
In mkoohafkan/wqptools: Outlier Detection Working Group Toolbox

Performs a Chi-squared test for multivariate outliers.

moutlier_chisq(
  xs,
  mask = !Reduce("|", lapply(xs, is.na)),
  threshold = c(0.9, 0.95),
  return.score = FALSE
)

`xs`	A dataframe or list of vectors (which will be coerced to a numeric matrix).
`mask`	A logical vector that defines which values in `x` will used when computing statistics. Useful when a subset of quality-assured data is available. Default mask is non-`NA` Values.
`threshold`	A length-two vector identifying thresholds for "mild" and "extreme" outliers.
`return.score`	if `TRUE`, return the numeric outlier score. If `FALSE`, return an ordered factor classifying the observations as one of "not outlier" (1), "mild outlier" (2), or "extreme outlier" (3).

x = seq(0, 34, by = 0.25)*pi
noise = rnorm(length(x), mean = 1, sd = 3)
y = sin(x) + noise
mask = noise < 1

moutlier_chisq(list(x, y))
moutlier_chisq(list(x, y), mask)
moutlier_chisq(list(x, y), mask, threshold = c(0.8, 0.9))
moutlier_chisq(list(x, y), return.score = TRUE)