Fitting the COM Poisson Binomial Distribution when binomial random variable, frequency, probability of success and v parameter are given
Fitting the COM Poisson Binomial Distribution when binomial random variable, frequency, probability of success and v parameter are given
The function will fit the COM Poisson Binomial Distribution when random variables, corresponding frequencies, probability of success and v parameter 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.
fitCOMPBin(x,obs.freq,p,v)
Arguments
x: vector of binomial random variables.
obs.freq: vector of frequencies.
p: single value for probability of success.
v: single value for v.
Returns
The output of fitCOMPBin gives the class format fitCPB 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.
fitCPB fitted probability values of dCOMPBin.
NegLL Negative Log Likelihood value.
p estimated probability value.
v estimated v 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.freq≥0x=0,1,2,..0<p<1−∞<v<+∞
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 variablesObs.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 itparameters <- EstMLECOMPBin(x=No.D.D,freq=Obs.fre.1,p=0.5,v=0.050)pCOMPBin <- bbmle::coef(parameters)[1]vCOMPBin <- bbmle::coef(parameters)[2]#fitting when the random variable,frequencies,probability and v parameter are givenresults <- fitCOMPBin(No.D.D,Obs.fre.1,pCOMPBin,vCOMPBin)results
#extracting the AIC valueAIC(results)#extract fitted valuesfitted(results)