cfS_Gaussian: Characteristic function of Normal distribution N(0,1)

Description Usage Arguments Value See Also Examples

Description

cfS_Gaussian(t) evaluates the characteristic function cf(t) of the symmetric zero-mean standard Gaussian distribution (i.e. the standard normal distribution with mean = 0 and variance = 1: N(0, 1)) cfS_Gaussian(t) = exp(-t^2/2)

Usage

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Arguments

t

numerical values (number, vector...)

Value

characteristic function cf(t) of the normal distribution N(0, 1)

See Also

For more details see WIKIPEDIA: https://en.wikipedia.org/wiki/Normal_distribution

Other Continuous Probability distribution: cfS_Arcsine, cfS_Beta, cfS_Rectangular, cfS_StudentT, cfS_Trapezoidal, cfS_Triangular, cfX_Beta, cfX_ChiSquared, cfX_Exponential, cfX_Gamma, cfX_InverseGamma, cfX_LogNormal, cfX_Normal, cfX_PearsonV, cfX_Rectangular, cfX_Triangular

Other Symetric Probability distribution: cfS_Arcsine, cfS_Rectangular, cfS_StudentT, cfS_Trapezoidal, cfS_Triangular

Examples

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## EXAMPLE1 (CF of the Gaussian distribution N(0,1))
t <- seq(-5, 5, length.out = 501)
plotGraf(function(t)
  cfS_Gaussian(t), t, title = "CF of the Gaussian distribution N(0,1)")

## EXAMPLE2 (PDF/CDF of the Gaussian distribution N(0,1))
cf <- function(t)
  cfS_Gaussian(t)
x <- seq(-4, 4, length.out = 101)
prob <- c(0.9, 0.95, 0.99)
result <- cf2DistGP(cf, x, prob, N = 2 ^ 5, SixSigmaRule = 8)

Simkova/CharFun documentation built on May 9, 2019, 1:30 p.m.