fitGammaBin function

Fitting the Gamma Binomial distribution when binomial random variable, frequency and shape parameters are given

Fitting the Gamma Binomial distribution when binomial random variable, frequency and shape parameters are given

The function will fit the Gamma Binomial Distribution when random variables, corresponding frequencies and shape parameters are given. It will provide the expected frequencies, chi-squared test statistics value, p value, degree of freedom and over dispersion value so that it can be seen if this distribution fits the data.

fitGammaBin(x,obs.freq,c,l)

Arguments

  • x: vector of binomial random variables.
  • obs.freq: vector of frequencies.
  • c: single value for shape parameter c.
  • l: single value for shape parameter l.

Returns

The output of fitGammaBin gives the class format fitGaB and fit consisting a list

bin.ran.var binomial random variables.

obs.freq corresponding observed frequencies.

exp.freq corresponding expected frequencies.

statistic chi-squared test statistics.

df degree of freedom.

p.value probability value by chi-squared test statistic.

fitMB fitted values of dGammaBin.

NegLL Negative Log Likelihood value.

c estimated value for shape parameter c.

l estimated value for shape parameter l.

AIC AIC value.

over.dis.para over dispersion value.

call the inputs of the function.

Methods summary, print, AIC, residuals and fitted can be used to extract specific outputs.

Details

0<c,l 0 < c,l x=0,1,2,... x = 0,1,2,... obs.freq0 obs.freq \ge 0

NOTE : If input parameters are not in given domain conditions necessary error messages will be provided to go further.

Examples

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 the parameters using maximum log likelihood value and assigning it parameters <- EstMLEGammaBin(x=No.D.D,freq=Obs.fre.1,c=0.1,l=0.1) cGBin <- bbmle::coef(parameters)[1] #assigning the estimated c lGBin <- bbmle::coef(parameters)[2] #assigning the estimated l #fitting when the random variable,frequencies,shape parameter values are given. results <- fitGammaBin(No.D.D,Obs.fre.1,cGBin,lGBin) results #extracting the expected frequencies fitted(results) #extracting the residuals residuals(results)

References

\insertRef grassia1977familyfitODBOD