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
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