View source: R/cf_TrapezoidalSymmetric.R
cf_TrapezoidalSymmetric | R Documentation |
cf_TrapezoidalSymmetric(t, lambda, coef, niid)
evaluates
the characteristic function of a linear combination (resp. convolution)
of independent zero-mean symmetric TRAPEZOIDAL random variables defined on the interval (-1,1)
.
That is, cf_TrapezoidalSymmetric
evaluates the characteristic function
cf(t)
of Y = sum_{i=1}^N coef_i * X_i
, where X_i ~ TrapezoidalSymmetric(\lambda_i)
are independent RVs defined on (-1,1)
, for all i = 1,...,N
.
The characteristic function of X ~ TrapezoidalSymmetric(\lambda)
, with
E(X) = 0
and Var(X) = (1+\lambda^2)/6
, is
cf(t) = cf_TrapezoidalSymmetric(t) = cf_RectangularSymmetric(w*t))*cf_RectangularSymmetric((1-w)*t) = (sin(w*t)/(w*t))*(sin((1-w)*t)/((1-w)*t)),
where w = (1+\lambda)/2
.
cf_TrapezoidalSymmetric(t, lambda, coef, niid)
t |
vector or array of real values, where the CF is evaluated. |
lambda |
parameter of the offset, |
coef |
vector of the coefficients of the linear combination
of the zero-mean symmetric TRAPEZOIDAL 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 a linear combination
of independent zero-mean symmetric TRAPEZOIDAL random variables.
Ver.: 16-Sep-2018 18:39:29 (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/Trapezoidal_distribution.
Other Continuous Probability Distribution:
cfS_Arcsine()
,
cfS_Beta()
,
cfS_Gaussian()
,
cfS_Laplace()
,
cfS_Rectangular()
,
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_TriangularSymmetric()
,
cf_vonMises()
Other Symmetric Probability Distribution:
cfS_Arcsine()
,
cfS_Beta()
,
cfS_Gaussian()
,
cfS_Laplace()
,
cfS_Rectangular()
,
cfS_Student()
,
cfS_Trapezoidal()
,
cf_ArcsineSymmetric()
,
cf_BetaSymmetric()
,
cf_RectangularSymmetric()
,
cf_TSPSymmetric()
## EXAMPLE 1
#CF of the symmetric Trapezoidal distribution with lambda = 1/2
lambda <- 1 / 2
t <- seq(from = -50,
to = 50,
length.out = 201)
plotReIm(function(t)
cf_TrapezoidalSymmetric(t, lambda), t,
title = "CF of the symmetric Trapezoidal distribution on (-1,1)")
## EXAMPLE 2
# CF of a linear combination of independent Trapezoidal RVs
t <- seq(from = -20,
to = 20,
length.out = 201)
lambda <- c(3, 3, 4, 4, 5) / 7
coef <- c(1, 2, 3, 4, 5) / 15
plotReIm(function(t)
cf_TrapezoidalSymmetric(t, lambda, coef), t,
title = "CF of a linear combination of independent Trapezoidal RVs")
## EXAMPLE 3
# PDF/CDF of a weighted linear combination of independent Trapezoidal RVs
lambda <- c(3, 3, 4, 4, 5) / 7
coef <- c(1, 2, 3, 4, 5) / 15
cf <- function(t)
cf_TrapezoidalSymmetric(t, lambda, coef)
x <- seq(from = -1,
to = 1,
length.out = 201)
prob <- c(0.9, 0.95, 0.99)
options <- list()
options$N <- 2 ^ 12
options$xMin <- -1
options$xMax <- 1
result <- cf2DistGP(cf, x, prob, options)
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