Utilities for the lognormal distribution in R
Compute moments.
Estimate autocorrelation.
Approximate the sum of correlated lognormals.
Moments and mode
Expected value and variance: getLognormMoments
Mode: getLognormMode
Median: getLognormMedian
Estimating parameters
from sample:
estimateParmsLognormFromSample
from mean and variance at original scale:
getParmsLognormForMoments
from mean and multiplicative standard deviation at original
scale: getParmsLognormForExpval
from expected value and upper quantile:
getParmsLognormForMeanAndUpper
from median and upper quantile:
getParmsLognormForMedianAndUpper
from mode and upper quantile:
getParmsLognormForModeAndUpper
from lower and upper quantile:
getParmsLognormForLowerAndUpper
Approximate the sum of correlated lognormals
According to Lo 2013: estimateSumLognormal
Utilities for correlated data. These functions maybe moved to a separate package in future.
Estimate standard error of the mean: seCor
Compute the effective number of observations taking into
account autocorrelation: computeEffectiveNumObs
Return the vector of effective components of the autocorrelation:
computeEffectiveAutoCorr
Estimate the variance of a correlated time series:
varEffective
Also have a look at the package vignettes.
Limpert E, Stahel W & Abbt M (2001) Log-normal Distributions across the Sciences:
Keys and Clues.BioScience, Oxford University Press (OUP), 51 , 341
10.1641/0006-3568(2001)051[0341:lndats]2.0.co;2
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