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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