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These functions calculate the scores according to:
score_z: Normal(z) distribution
score_z
score_mad: Mean absolute deviation
score_mad
score_t: t-distribution
score_t
score_chi: chi-distribution
score_chi
score_z(x, na.rm = getOption("transx.na.rm"))score_mad(x, na.rm = getOption("transx.na.rm"))score_t(x, na.rm = getOption("transx.na.rm"))score_chisq(x, na.rm = getOption("transx.na.rm"))
score_mad(x, na.rm = getOption("transx.na.rm"))
score_t(x, na.rm = getOption("transx.na.rm"))
score_chisq(x, na.rm = getOption("transx.na.rm"))
[univariate vector]
Univariate vector, numeric or ts object with only one dimension.
[logical(1): getOption("transx.na.rm")]
A value indicating whether NA values should be stripped before the computation proceeds.
Returns a vector with the same class and attributes as the input vector.
Because function are known with different names:
score_z is identical to std_mean
std_mean
score_mad is identical to std_median
std_median
scores
# NOT RUN { x <- seq(-3,3,0.5) score_z(x) score_mad(x) score_t(x) # }
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