34 lines
No EOL
1 KiB
R
34 lines
No EOL
1 KiB
R
computePopulationLogml <- function(pops, adjprior, priorTerm = 0) {
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# Palauttaa length(pops)*1 taulukon, jossa on laskettu korikohtaiset
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# ======================================================== #
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# Limiting COUNTS size #
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# ======================================================== #
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COUNTS <- COUNTS[seq_len(nrow(adjprior)), seq_len(ncol(adjprior)), pops, drop=FALSE]
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x <- size(COUNTS, 1)
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y <- size(COUNTS, 2)
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z <- length(pops)
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# ======================================================== #
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# Computation #
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# ======================================================== #
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term1 <- squeeze(
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# FIXME: assumes COUNTS has 3 dims. Where does this come from?
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sum(
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sum(
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reshape(
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lgamma(
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repmat(adjprior, c(1, 1, length(pops))) +
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COUNTS[seq_len(nrow(adjprior)), seq_len(ncol(adjprior)), pops, drop=FALSE]
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),
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c(x, y, z)
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),
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1
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),
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2
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)
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)
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popLogml <- term1 - sum(lgamma(1 + SUMCOUNTS[pops, ]), 2) - priorTerm
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return(popLogml)
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} |