Fit bivariate copula for normal mixture models
fit.NGS.nmix.copula(x,y,mle.large=FALSE,gridsize=101)
fit.nmix.copula(x,y,mle.large=FALSE,gridsize=101)
fit.GLD.copula(x,y,mle.large=FALSE,gridsize=101)
fit.mlnorm.copula(x,y,mle.large=FALSE,gridsize=101,k=2)
Two Next-Generation Sequencing data with same structures
Default ,mle.large=FALSE
, don't use the big
two-way histogram to find MLE.
The size of the grid in the xy-plane to evaluate the joint density.
number of components
the two profiles need to be sent as parameters. We don't need to fit the normal mixture outside the function. But we need to fit normal mixture model for NGS data withinin the function to get the histograms, and the counts within two 2x2 tables. The output include 1) the two fitted model, and 2) estimated parameter Psi. In addition, we show 3) the Psi's used to search for the optimal Psi, and 4) Chi-square test statistics, and 5) the correponding p-values. In addition, we also find 6) the MLE of Psi, and 7) its Chi-square test statistic and 8) p-value.
to be updated
# NOT RUN {
# To be updated.
# }
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