fitCOMPBin | R Documentation |
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)
x |
vector of binomial random variables. |
obs.freq |
vector of frequencies. |
p |
single value for probability of success. |
v |
single value for v. |
obs.freq \ge 0
x = 0,1,2,..
0 < p < 1
-\infty < v < +\infty
NOTE : If input parameters are not in given domain conditions necessary error messages will be provided to go further.
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.
borges2014poissonfitODBOD
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 <- 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 given
results <- fitCOMPBin(No.D.D,Obs.fre.1,pCOMPBin,vCOMPBin)
results
#extracting the AIC value
AIC(results)
#extract fitted values
fitted(results)
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