Description Usage Arguments Value See Also Examples
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)
1 |
t |
numerical values (number, vector...) |
characteristic function cf(t) of the normal distribution N(0, 1)
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
1 2 3 4 5 6 7 8 9 10 11 | ## 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)
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