fitCorrBin: Fitting the Correlated Binomial Distribution when binomial...

Description Usage Arguments Details Value References Examples

View source: R/CorrBin.R

Description

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.

Usage

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

Arguments

x

vector of binomial random variables

obs.freq

vector of frequencies

p

single value for probability of success

cov

single value for covariance

print

logical value for print or not

Details

obs.freq ≥ 0

x = 0,1,2,..

0 < p < 1

-∞ < cov < +∞

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

Value

The output of fitCorrBin gives a list format consisting

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

References

Johnson, N. L., Kemp, A. W., & Kotz, S. (2005). Univariate discrete distributions (Vol. 444). Hoboken, NJ: Wiley-Interscience.

L. L. Kupper, J.K.H., 1978. The Use of a Correlated Binomial Model for the Analysis of Certain Toxicological Experiments. Biometrics, 34(1), pp.69-76.

Paul, S.R., 1985. A three-parameter generalization of the binomial distribution. Communications in Statistics - Theory and Methods, 14(6), pp.1497-1506.

Available at: http://www.tandfonline.com/doi/abs/10.1080/03610928508828990 .

Jorge G. Morel and Nagaraj K. Neerchal. Overdispersion Models in SAS. SAS Institute, 2012.

Examples

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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=suppressWarnings(bbmle::mle2(EstMLECorrBin,start = list(p=0.5,cov=0.0050),
           data = list(x=No.D.D,freq=Obs.fre.1)))
pCorrBin=bbmle::coef(parameters)[1]
covCorrBin=bbmle::coef(parameters)[2]
#fitting when the random variable,frequencies,probability and covariance are given
fitCorrBin(No.D.D,Obs.fre.1,pCorrBin,covCorrBin)
#extracting the expected frequencies
fitCorrBin(No.D.D,Obs.fre.1,pCorrBin,covCorrBin,FALSE)$exp.freq

Amalan-ConStat/R-fitODBOD documentation built on Oct. 1, 2018, 7:13 p.m.