Functions for the Lognormal Distribution

---

Documentation for package ‘lognorm’ version 0.1.10

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

computeEffectiveAutoCorr	Estimate vector of effective components of the autocorrelation
computeEffectiveNumObs	Compute the effective number of observations taking into account autocorrelation
estimateDiffLognormal	Inference on the difference of two lognormals
estimateParmsLognormFromSample	Estimate lognormal distribution parameters from a sample
estimateStdErrParms	Estimate lognormal distribution parameters from a sample
estimateSumLognormal	Estimate the parameters of the lognormal approximation to the sum
estimateSumLognormalSample	Estimate the parameters of the lognormal approximation to the sum
estimateSumLognormalSampleExpScale	Estimate the parameters of the lognormal approximation to the sum
getCorrMatFromAcf	Construct the full correlation matrix from autocorrelation components.
getLognormMedian	Compute summary statistics of a log-normal distribution
getLognormMode	Compute summary statistics of a log-normal distribution
getLognormMoments	Compute summary statistics of a log-normal distribution
getParmsLognormForExpval	Calculate mu and sigma of lognormal from summary statistics.
getParmsLognormForLowerAndUpper	Calculate mu and sigma of lognormal from summary statistics.
getParmsLognormForLowerAndUpperLog	Calculate mu and sigma of lognormal from summary statistics.
getParmsLognormForMeanAndUpper	Calculate mu and sigma of lognormal from summary statistics.
getParmsLognormForMedianAndUpper	Calculate mu and sigma of lognormal from summary statistics.
getParmsLognormForModeAndUpper	Calculate mu and sigma of lognormal from summary statistics.
getParmsLognormForMoments	Calculate mu and sigma of lognormal from summary statistics.
pDiffLognormalSample	Inference on the difference of two lognormals
scaleLogToOrig	Scale standard deviation between log and original scale.
scaleOrigToLog	Scale standard deviation between log and original scale.
seCor	Compute the standard error accounting for empirical autocorrelations
setMatrixOffDiagonals	set off-diagonal values of a matrix
varCor	Compute the unbiased variance accounting for empirical autocorrelations