After fitting the distribution using this function we can extract the overdispersion value. This function works for fitTriBin, fitBetaBin, fitKumBin, fitGHGBB and fitMcGBB for Binomial Mixture Distributions. Similarly, Alternate Binomial Distributions also support this function for fitAddBin,fitBetaCorrBin, fitCOMPBin, fitCorrBin and fitMultiBin.
Overdispersion(object)
object | An object from one of the classes of fitTB,fitBB,fitKB,fitGB,fitMB. |
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The output of Overdispersion
gives a single value which is the
overdispersion.
Note : Only objects from classes of above mentioned classes can be used.
No.D.D=0:7 #assigning the random variables Obs.fre.1=c(47,54,43,40,40,41,39,95) #assigning the corresponding frequencies #estimating mode value for given data results<-EstMLETriBin(No.D.D,Obs.fre.1) results#> Call: #> .EstMLETriBin(x = x, freq = freq) #> #> Coefficient : #> mode #> 0.944444mode<-results$mode #fitting the Triangular Bionomial distribution for estimated parameters TriBin<-fitTriBin(No.D.D,Obs.fre.1,mode) TriBin#> Call: #> fitTriBin(x = No.D.D, obs.freq = Obs.fre.1, mode = mode) #> #> Chi-squared test for Triangular Binomial Distribution #> #> Observed Frequency : 47 54 43 40 40 41 39 95 #> #> expected Frequency : 11.74 23.47 35.21 46.94 58.66 70.2 79.57 73.21 #> #> estimated Mode value: 0.944444 #> #> X-squared : 193.6159 ,df : 6 ,p-value : 0 #> #> over dispersion : 0.2308269#extracting the overdispersion Overdispersion(TriBin)#> [1] 0.2308269