lognorm (version 0.1.6)

estimateSumLognormal: estimateSumLognormal

Description

Estimate the distribution parameters of the lognormal approximation to the sum

Usage

estimateSumLognormal(mu, sigma, corr = Diagonal(length(mu)), 
    sigmaSum = numeric(0), corrLength = if (inherits(corr, 
        "ddiMatrix")) 0 else nTerm, isStopOnNoTerm = FALSE, 
    effAcf, na.rm = isStopOnNoTerm)

Arguments

mu

numeric vector of center parameters of terms at log scale

sigma

numeric vector of variance parameter of terms at log scale

corr

numeric matrix of correlations between the random variables

sigmaSum

numeric scalar: possibility to specify of a precomputed scale parameter

corrLength

integer scalar: set correlation length to smaller values to speed up computation by neglecting correlations among terms further apart. Set to zero to omit correlations.

isStopOnNoTerm

if no finite estimate is provided then by default NA is returned for the sum. Set this to TRUE to issue an error instead.

effAcf

numeric vector of effective autocorrelation This overrides arguments corr and corrLength

na.rm

if there are terms with NA values in mu or sigma by default also the sum coefficients are NA. Set to TRUE to neglect such terms in the sum.

Value

numeric vector with two components mu and sigma the parameters of the lognormal distribution at log scale

References

Lo C (2013) WKB approximation for the sum of two correlated lognormal random variables. Applied Mathematical Sciences, Hikari, Ltd., 7 , 6355-6367 10.12988/ams.2013.39511

Examples

# NOT RUN {
# distribution of the sum of two lognormally distributed random variables
mu1 = log(110)
mu2 = log(100)
sigma1 = log(1.2)
sigma2 = log(1.6)
(coefSum <- estimateSumLognormal( c(mu1,mu2), c(sigma1,sigma2) ))
# repeat with correlation
(coefSumCor <- estimateSumLognormal( c(mu1,mu2), c(sigma1,sigma2), effAcf = c(1,0.9) ))
# expected value is equal, but variance with correlated variables is larger
getLognormMoments(coefSum["mu"],coefSum["sigma"])
getLognormMoments(coefSumCor["mu"],coefSumCor["sigma"])
# }