Description Usage Arguments Details Value Note See Also Examples
View source: R/NB.plot.likelihood.R
This function does not maximise the likelihood function but rather provide a range of log-likelihood values as a function of effective population size.
1 | NB.plot.likelihood(infile, alleles, sample.interval, lb, ub, step, plotit = TRUE)
|
infile |
The input data. Please refer to |
alleles |
Number of alleles at each locus. Please refer to |
sample.interval |
Please refer to |
lb |
The lower bound of N. |
ub |
The upper bound of N. |
step |
How many points do you want to evaluate at. |
plotit |
Do you want to plot the log-likelihood out? |
The input arguments infile
, alleles
, and sample.interval
have the same definitions as those in NB.estimator
.
Returns a range of log-likelihood values with the associated effective population size. If plotit==TRUE
then a plot of the log-likelihood will also be produced.
This would be a good way to examine whether the maximization converges to the global maximum.
1 2 3 4 5 6 | ## CREATE SAMPLE DATASET
NB.example.dataset()
## PLOT THE LOG-LIKELIHOOD
NB.plot.likelihood(infile='sample_data.txt', alleles=rep(4, 50),
sample.interval=c(0, 8), lb=300, ub=2000, step=200)
|
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