BMTdispersion {BMT} | R Documentation |
The BMT Distribution Descriptive Measures - Dispersion.
Description
Variance, standard deviation and interquantile range for the BMT
distribution, with p3
and p4
tails weights (\kappa_l
and \kappa_r
) or asymmetry-steepness parameters (\zeta
and
\xi
) and p1
and p2
domain (minimum and maximum) or
location-scale (mean and standard deviation) parameters.
Usage
BMTvar(p3, p4, type.p.3.4 = "t w", p1 = 0, p2 = 1, type.p.1.2 = "c-d")
BMTsd(p3, p4, type.p.3.4 = "t w", p1 = 0, p2 = 1, type.p.1.2 = "c-d")
BMTiqr(p3, p4, type.p.3.4 = "t w", p1 = 0, p2 = 1, type.p.1.2 = "c-d")
Arguments
p3 , p4 |
tails weights ( |
type.p.3.4 |
type of parametrization asociated to p3 and p4. "t w" means tails weights parametrization (default) and "a-s" means asymmetry-steepness parametrization. |
p1 , p2 |
domain (minimum and maximum) or location-scale (mean and standard deviation) parameters of the BMT ditribution. |
type.p.1.2 |
type of parametrization asociated to p1 and p2. "c-d" means domain parametrization (default) and "l-s" means location-scale parametrization. |
Details
See References.
Value
BMTvar
gives the variance, BMTsd
the standard deviation
and BMTiqr
the interquantile range for the BMT distribution.
The arguments are recycled to the length of the result. Only the first
elements of type.p.3.4
and type.p.1.2
are used.
If type.p.3.4 == "t w"
, p3 < 0
and p3 > 1
are errors
and return NaN
.
If type.p.3.4 == "a-s"
, p3 < -1
and p3 > 1
are errors
and return NaN
.
p4 < 0
and p4 > 1
are errors and return NaN
.
If type.p.1.2 == "c-d"
, p1 >= p2
is an error and returns
NaN
.
If type.p.1.2 == "l-s"
, p2 <= 0
is an error and returns
NaN
.
Author(s)
Camilo Jose Torres-Jimenez [aut,cre] cjtorresj@unal.edu.co
References
Torres-Jimenez, C. J. and Montenegro-Diaz, A. M. (2017, September), An alternative to continuous univariate distributions supported on a bounded interval: The BMT distribution. ArXiv e-prints.
Torres-Jimenez, C. J. (2018), The BMT Item Response Theory model: A new skewed distribution family with bounded domain and an IRT model based on it, PhD thesis, Doctorado en ciencias - Estadistica, Universidad Nacional de Colombia, Sede Bogota.
See Also
BMTcentral
, BMTskewness
,
BMTkurtosis
, BMTmoments
for other descriptive
measures or moments.
Examples
# BMT on [0,1] with left tail weight equal to 0.25 and
# right tail weight equal to 0.75
BMTvar(0.25, 0.75, "t w")
BMTsd(0.25, 0.75, "t w")
BMTiqr(0.25, 0.75, "t w")
# BMT on [0,1] with asymmetry coefficient equal to 0.5 and
# steepness coefficient equal to 0.75
BMTvar(0.5, 0.5, "a-s")
BMTsd(0.5, 0.5, "a-s")
BMTiqr(0.5, 0.5, "a-s")
# BMT on [-1.783489,3.312195] with left tail weight equal to 0.25 and
# right tail weight equal to 0.75
BMTvar(0.25, 0.75, "t w", -1.783489, 3.312195, "c-d")
BMTsd(0.25, 0.75, "t w", -1.783489, 3.312195, "c-d")
BMTiqr(0.25, 0.75, "t w", -1.783489, 3.312195, "c-d")
# BMT with mean equal to 0, standard deviation equal to 1,
# asymmetry coefficient equal to 0.5 and
# steepness coefficient equal to 0.75
BMTvar(0.5, 0.5, "a-s", 0, 1, "l-s")
BMTsd(0.5, 0.5, "a-s", 0, 1, "l-s")
BMTiqr(0.5, 0.5, "a-s", 0, 1, "l-s")