simulTransTrees: Simultaneously infer transmission trees given phylogenetic...
In JamesStimson/transnp: Transmission inference using SNP data

Description Usage Arguments Value

Simultaneously infer transmission trees given phylogenetic trees constructed from clusters of sequences. Wrapper for infer_multiTTree_shareParam, taking mean and std deviations rather than shape and scale for the Gamma parameters

simulTransTrees(timedTrees, mean_gen = 1, stddev_gen = 1, mean_sample = 1,
  stddev_sample = 1, share = c("neg", "off.r", "off.p", "pi"),
  mcmcIterations = nIter, startNeg = 1, startOff.p = 0.8,
  startOff.r = 1, startPi = 0.9, updateNeg = T, updatePi = F,
  updateOff.p = FALSE)

`mean_gen`	Mean of the Gamma probability density function representing the generation time
`stddev_gen`	Standard deviation of the Gamma probability density function representing the generation time
`mean_sample`	Mean of the Gamma probability density function representing the sampling time
`stddev_sample`	Standard deviation of the Gamma probability density function representing the sampling time
`share`	Character vector of parameters to be shared. For example, share = c("off.r", "off.p") would share the offspring distribution. Allowed parameter names are "neg", "off.r", "off.p" and "pi".
`mcmcIterations`	Number of MCMC iterations to run the algorithm for
`startNeg`	Starting value of within-host coalescent parameter Ne*g
`startOff.p`	Starting value of parameter off.p
`startOff.r`	Starting value of parameter off.r
`startPi`	Starting value of sampling proportion pi
`updateNeg`	Whether of not to update the parameter Ne*g
`updatePi`	Whether or not to update the parameter pi
`updateOff.p`	Whether or not to update the parameter off.p
`ptree_lst`	List of phylogenetic tree
`thinning`	MCMC thinning interval between two sampled iterations
`updateOff.r`	Whether or not to update the parameter off.r
`startCTree_lst`	Optional combined list of trees to start from
`updateTTree`	Whether or not to update the transmission tree
`optiStart`	Whether or not to optimise the MCMC start point
`dateT`	Date when process stops (this can be Inf for fully simulated outbreaks)