Description Usage Arguments Details Value Author(s) See Also Examples
Given the parameters of a χ^2 distribution, aout.chisq
identifies α-outliers in a given data set.
1 2 3 4 | aout.chisq(data, param, alpha = 0.1, hide.outliers = FALSE, ncp = 0, lower = auto.l,
upper = auto.u, method.in = "Newton", global.in = "gline",
control.in = list(sigma = 0.1, maxit = 1000, xtol = 1e-12,
ftol = 1e-12, btol = 1e-04))
|
data |
a vector. The data set to be examined. |
param |
an atomic vector. Contains the degrees of freedom of the χ^2 distribution. |
alpha |
an atomic vector. Determines the maximum amount of probability mass the outlier region may contain. Defaults to 0.1. |
hide.outliers |
boolean. Returns the outlier-free data if set to |
ncp |
an atomic vector. Determines the non-centrality parameter of the χ^2 distribution. Defaults to 0. |
lower |
an atomic vector. First element of |
upper |
an atomic vector. Second element of |
method.in |
See |
global.in |
See |
control.in |
See |
The α-outlier region of a χ^2 distribution is generally not available in closed form or via the tails, such that a non-linear equation system has to be solved.
Data frame of the input data and an index named is.outlier
that flags the outliers with TRUE
. If hide.outliers is set to TRUE
, a simple vector of the outlier-free data.
A. Rehage
1 | aout.chisq(chisq.test(occupationalStatus)$statistic, 49)
|
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