fitCorrBin function

Fitting the Correlated Binomial Distribution when binomial random variable, frequency, probability of success and covariance are given

Fitting the Correlated Binomial Distribution when binomial random variable, frequency, probability of success and covariance are given

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

fitCorrBin(x,obs.freq,p,cov)

Arguments

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

Returns

The output of fitCorrBin gives the class format fitCB 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.

corr Correlation value.

fitCB fitted probability values of dCorrBin.

NegLL Negative Log Likelihood 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 <cov<+ -\infty < cov < +\infty

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 <- EstMLECorrBin(x=No.D.D,freq=Obs.fre.1,p=0.5,cov=0.0050) pCorrBin <- bbmle::coef(parameters)[1] covCorrBin <- bbmle::coef(parameters)[2] #fitting when the random variable,frequencies,probability and covariance are given results <- fitCorrBin(No.D.D,Obs.fre.1,pCorrBin,covCorrBin) results #extracting the AIC value AIC(results) #extract fitted values fitted(results)

References

\insertRef johnson2005univariatefitODBOD

\insertRef kupper1978usefitODBOD

\insertRef paul1985threefitODBOD

\insertRef morel2012overdispersionfitODBOD