score: Score transformation

In kvasilopoulos/transx: Transform Univariate Time Series

Description

These functions calculate the scores according to:

• score_z: Normal(z) distribution

• score_mad: Mean absolute deviation

• score_t: t-distribution

• score_chi: chi-distribution

Usage

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"))

Arguments

x	[univariate vector] Univariate vector, numeric or ts object with only one dimension.
na.rm	[logical(1): getOption("transx.na.rm")] A value indicating whether NA values should be stripped before the computation proceeds.

Details

Because function are known with different names:

• score_z is identical to std_mean

• score_mad is identical to std_median

Value

Returns a vector with the same class and attributes as the input vector.

See Also

scores

Examples

x <- seq(-3,3,0.5)
score_z(x)
score_mad(x)
score_t(x)

kvasilopoulos/transx documentation built on Jan. 26, 2021, 6:14 p.m.