[R] lmom package

[Katherine Gobin]

Dear R Forum
I have a set of data say as given below and as an exercise of trying to fit statistical distribution to this data, I am estimating parameters. 
amounts =  c(38572.5599129508,11426.6705314315,21974.1571641187,118530.32782443,3735.43055996748,66309.5211176106,72039.2934132668,21934.8841708626,78564.9136114375,1703.65825161293,2116.89180930203,11003.495671332,19486.3296339113,1871.35861218795,6887.53851253407,148900.978055447,7078.56497101651,79348.1239806592,20157.6241066905,1259.99802108593,3934.45912233674,3297.69946631591,56221.1154121067,13322.0705174134,45110.2498756567,31910.3686613912,3196.71168501252,32843.0140437202,14615.1499458453,13013.9915051561,116104.176753387,7229.03056392023,9833.37962177814,2882.63239493673,165457.372543821,41114.066453219,47188.1677766245,25708.5883755617,82703.7378298092,8845.04197017415,844.28834047836,35410.8486123933,19446.3808445684,17662.2398792892,11882.8497070776,4277181.17817307,30239.0371267968,45165.7512343364,22102.8513746687,5988.69296597127,51345.0146170238,1275658.35495898,15260.4892854214,8861.76578480635,37647.1638704867,4979.53544046949,7012.48134772332,3385.20612391205,1911.03114395959,66886.5036605189,2223.47536156462,814.947809578378,234.028589468841,5397.4347625133,13346.3226579065,28809.3901352898,6387.69226236731,5639.42730553242,2011100.92675507,4150.63707173462,34098.7514446498,3437.10672573502,289710.315303182,8664.66947305203,13813.3867161134,208817.521491857,169317.624400274,9966.78447705792,37811.1721605562,2263.19211279927,80434.5581206454,19057.8093104899,24664.5067589624,25136.5042354789,3582.85741610706,6683.13898432794,65423.9991390846,134848.302304064,3018.55371579808,546249.641168158,172926.689143006,3074.15064180208,1521.70624812788,59012.4248281661,21226.928522236,17572.5682970983,226.646947337851,56232.2982652019,14641.0043361533,6997.94414914865)
library(lmom)lmom           <- samlmu(amounts)

# ____________________________________________________
# Normal distribution
parameters_of_NOR  <- pelnor(lmom); parameters_of_NOR

> parameters_of_NOR  <- pelnor(lmom); parameters_of_NOR      mu        sigma 115148.4  175945.8 

# Minitab and SPSS parameter values                              Location                    Scale
Minitab              115148.4                 485173SPSS                 115148.4                 485173           
# __________________________________________________________

# Log normal 3 parameter distribution parameters_of_LN3  <- pelln3(lmom); parameters_of_LN3

> parameters_of_LN3  <- pelln3(lmom); parameters_of_LN3
       zeta              mu                sigma 3225.798890    9.114879     2.240841
                               Location             Scale                  ShapeMinitab                  9.73361             1.76298               75.51864SPSS                    9.7336                1.763                    75.519         

Similarly besides Generalized extreme Value distribution, all the parameter values vary significantly than parameter values obtained using Minitab and SPSS. In case of Normal distribution, the dispersion parameter is simply sample standard deviation and excel also gives the parameter value 485172.8 and varies significantly than what we get from R.
And parameter values do differ even for many other distributions too viz. Gamma distribution etc.
Is there any different algorithm or logic used in R? Can someone please guide.?
Regards
Katherine


	[[alternative HTML version deleted]]