fitMultiBin function

Fitting the Multiplicative Binomial Distribution when binomial random variable, frequency, probability of success and theta parameter are given

Fitting the Multiplicative Binomial Distribution when binomial random variable, frequency, probability of success and theta parameter are given

The function will fit the Multiplicative Binomial distribution when random variables, corresponding frequencies, probability of success and theta parameter are given. It will provide the expected frequencies, chi-squared test statistics value, p value and degree of freedom value so that it can be seen if this distribution fits the data.

fitMultiBin(x,obs.freq,p,theta)

Arguments

  • x: vector of binomial random variables.
  • obs.freq: vector of frequencies.
  • p: single value for probability of success.
  • theta: single value for theta parameter.

Returns

The output of fitMultiBin gives the class format fitMuB 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.

fitMuB fitted probability values of dMultiBin.

NegLL Negative Log Likelihood value.

p estimated probability value.

theta estimated theta parameter value.

AIC AIC value.

call the inputs of the function.

Methods summary, print, AIC, residuals and fitted

can be used to extract specific outputs.

Details

obs.freq0 obs.freq \ge 0 x=0,1,2,.. x = 0,1,2,.. 0<p<1 0 < p < 1 0<theta 0 < theta

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 <- EstMLEMultiBin(x=No.D.D,freq=Obs.fre.1,p=0.1,theta=.3) pMultiBin <- bbmle::coef(parameters)[1] #assigning the estimated probability value thetaMultiBin <- bbmle::coef(parameters)[2] #assigning the estimated theta value #fitting when the random variable,frequencies,probability and theta are given results <- fitMultiBin(No.D.D,Obs.fre.1,pMultiBin,thetaMultiBin) results #extracting the AIC value AIC(results) #extract fitted values fitted(results)

References

\insertRef johnson2005univariatefitODBOD

\insertRef kupper1978usefitODBOD

\insertRef paul1985threefitODBOD

See Also

mle2