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Fit a finite normal mixture model for pre-binned NGS data
fit.NGS(x, iter.max=30,reflect=TRUE)
Next-Generation Sequencing data or similar. Could have a lot of zeros but negative values are not allowed
maximum iteration to find the optimal fit.
Use reflect and replicate method to adjust for boundary effect.
We fit a mixture model to take care the zero values using component-0.
AS 254, ...
# NOT RUN { # To be updated. x = rexp(100,1) x = c(rep(0,20),x) out = fit.NGS(x) plot(out) # }
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