View source: R/cfS_Rectangular.R
cfS_Rectangular | R Documentation |
cfS_Rectangular(t, coef, niid)
evaluates the characteristic function cf(t)
of the zero-mean symmetric RECTANGULAR distribution defined on the interval (-1,1)
.
cfS_Rectangular
is an ALIAS of the more general function
cf_RectangularSymmetric
, used to evaluate the characteristic function
of a linear combination of independent RECTANGULAR distributed random variables.
The characteristic function of X ~ RectangularSymmetric
is defined by
cf(t) = sinc(t) = sin(t)/t.
cfS_Rectangular(t, coef, niid)
t |
vector or array of real values, where the CF is evaluated. |
coef |
vector of coefficients of the linear combination of Rectangular distributed random variables.
If coef is scalar, it is assumed that all coefficients are equal. If empty, default value is |
niid |
scalar convolution coeficient. |
Characteristic function cf(t)
of the zero-mean symmetric RECTANGULAR distribution.
Ver.: 16-Sep-2018 19:09:05 (consistent with Matlab CharFunTool v1.3.0, 02-Jun-2017 12:08:24).
WITKOVSKY V. (2016). Numerical inversion of a characteristic function: An alternative tool to form the probability distribution of output quantity in linear measurement models. Acta IMEKO, 5(3), 32-44.
For more details see WIKIPEDIA: https://en.wikipedia.org/wiki/Uniform_distribution_(continuous).
Other Continuous Probability Distribution:
cfS_Arcsine()
,
cfS_Beta()
,
cfS_Gaussian()
,
cfS_Laplace()
,
cfS_Student()
,
cfS_TSP()
,
cfS_Trapezoidal()
,
cfS_Triangular()
,
cfS_Wigner()
,
cfX_ChiSquare()
,
cfX_Exponential()
,
cfX_FisherSnedecor()
,
cfX_Gamma()
,
cfX_InverseGamma()
,
cfX_LogNormal()
,
cf_ArcsineSymmetric()
,
cf_BetaNC()
,
cf_BetaSymmetric()
,
cf_Beta()
,
cf_ChiSquare()
,
cf_Exponential()
,
cf_FisherSnedecorNC()
,
cf_FisherSnedecor()
,
cf_Gamma()
,
cf_InverseGamma()
,
cf_Laplace()
,
cf_LogRV_BetaNC()
,
cf_LogRV_Beta()
,
cf_LogRV_ChiSquareNC()
,
cf_LogRV_ChiSquare()
,
cf_LogRV_FisherSnedecorNC()
,
cf_LogRV_FisherSnedecor()
,
cf_LogRV_MeansRatioW()
,
cf_LogRV_MeansRatio()
,
cf_LogRV_WilksLambdaNC()
,
cf_LogRV_WilksLambda()
,
cf_Normal()
,
cf_RectangularSymmetric()
,
cf_Student()
,
cf_TSPSymmetric()
,
cf_TrapezoidalSymmetric()
,
cf_TriangularSymmetric()
,
cf_vonMises()
Other Symmetric Probability Distribution:
cfS_Arcsine()
,
cfS_Beta()
,
cfS_Gaussian()
,
cfS_Laplace()
,
cfS_Student()
,
cfS_Trapezoidal()
,
cf_ArcsineSymmetric()
,
cf_BetaSymmetric()
,
cf_RectangularSymmetric()
,
cf_TSPSymmetric()
,
cf_TrapezoidalSymmetric()
## EXAMPLE1
# CF of the Rectangular distribution on (-1,1)
t <- seq(-50, 50, length.out = 501)
plotReIm(function(t)
cfS_Rectangular(t), t, title = "CF of the Rectangular distribution on (-1,1)")
## EXAMPLE2
# PDF/CDF of the Rectangular distribution on (-1,1)
cf <- function(t)
cfS_Rectangular(t)
x <- seq(-2, 2, length.out = 101)
xRange <- 2
options <- list()
options$N <- 2 ^ 5
options$dx <- 2 / pi / xRange
result <- cf2DistGP(cf = cf, x = x, options = options)
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