Package: lognorm 0.1.9

lognorm: Functions for the Lognormal Distribution

The lognormal distribution (Limpert et al. (2001) <doi:10.1641/0006-3568(2001)051%5B0341:lndats%5D2.0.co;2>) can characterize uncertainty that is bounded by zero. This package provides estimation of distribution parameters, computation of moments and other basic statistics, and an approximation of the distribution of the sum of several correlated lognormally distributed variables (Lo 2013 <doi:10.12988/ams.2013.39511>) and the approximation of the difference of two correlated lognormally distributed variables (Lo 2012 <doi:10.1155/2012/838397>).

Authors:Thomas Wutzler

lognorm_0.1.9.tar.gz
lognorm_0.1.9.zip(r-4.7)lognorm_0.1.9.zip(r-4.6)lognorm_0.1.9.zip(r-4.5)
lognorm_0.1.9.tgz(r-4.6-any)lognorm_0.1.9.tgz(r-4.5-any)
lognorm_0.1.9.tar.gz(r-4.7-any)lognorm_0.1.9.tar.gz(r-4.6-any)
lognorm_0.1.9.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
lognorm/json (API)
NEWS

# Install 'lognorm' in R:
install.packages('lognorm', repos = c('https://bgctw.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/bgctw/lognorm/issues

On CRAN:

Conda:

5.75 score 6 stars 63 scripts 277 downloads 25 exports 2 dependencies

Last updated from:9cc622e5e3. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK139
source / vignettesOK187
linux-release-x86_64OK114
macos-release-arm64OK101
macos-oldrel-arm64OK87
windows-develOK116
windows-releaseOK87
windows-oldrelOK95
wasm-releaseOK105

Exports:computeEffectiveAutoCorrcomputeEffectiveNumObsestimateDiffLognormalestimateParmsLognormFromSampleestimateStdErrParmsestimateSumLognormalestimateSumLognormalSampleestimateSumLognormalSampleExpScalegetCorrMatFromAcfgetLognormMediangetLognormModegetLognormMomentsgetParmsLognormForExpvalgetParmsLognormForLowerAndUppergetParmsLognormForLowerAndUpperLoggetParmsLognormForMeanAndUppergetParmsLognormForMedianAndUppergetParmsLognormForModeAndUppergetParmsLognormForMomentspDiffLognormalSamplescaleLogToOrigscaleOrigToLogseCorsetMatrixOffDiagonalsvarCor

Dependencies:latticeMatrix

Approximating the difference of two lognormal random variables

Rendered fromlognormalDiff.Rmdusingknitr::rmarkdownon May 27 2026.

Last update: 2021-03-10
Started: 2020-06-30

Approximating the sum of lognormal random variables

Rendered fromlognormalSum.Rmdusingknitr::rmarkdownon May 27 2026.

Last update: 2021-03-10
Started: 2018-08-07

Using the lognorm package

Rendered fromlognorm.Rmdusingknitr::rmarkdownon May 27 2026.

Last update: 2021-03-10
Started: 2018-08-07

Readme and manuals

Help Manual

Help pageTopics
Estimate vector of effective components of the autocorrelationcomputeEffectiveAutoCorr
Compute the effective number of observations taking into account autocorrelationcomputeEffectiveNumObs
Inference on the difference of two lognormalsestimateDiffLognormal pDiffLognormalSample
Estimate lognormal distribution parameters from a sampleestimateParmsLognormFromSample estimateStdErrParms
Estimate the parameters of the lognormal approximation to the sumestimateSumLognormal estimateSumLognormalSample estimateSumLognormalSampleExpScale
Construct the full correlation matrix from autocorrelation components.getCorrMatFromAcf
Compute summary statistics of a log-normal distributiongetLognormMedian getLognormMode getLognormMoments
Calculate mu and sigma of lognormal from summary statistics.getParmsLognormForExpval getParmsLognormForLowerAndUpper getParmsLognormForLowerAndUpperLog getParmsLognormForMeanAndUpper getParmsLognormForMedianAndUpper getParmsLognormForModeAndUpper getParmsLognormForMoments
Scale standard deviation between log and original scale.scaleLogToOrig scaleOrigToLog
Compute the standard error accounting for empirical autocorrelationsseCor
set off-diagonal values of a matrixsetMatrixOffDiagonals
Compute the unbiased variance accounting for empirical autocorrelationsvarCor