joint.negllSS.flex: joint likelihod from a competition experiment and initial...

In javirudolph/StabilityToolkit: Statistical inference for bacterial stability assays

Description

Uses data from a competition experiment starting with an initial fraction of 0.5 and from a stability assay to compute the joint negative log-likelihood for the Segregation Selection model, under binomial sampling

Usage

joint.negllSS.flex(
  parm,
  data.compet,
  data.stabexp,
  nrc,
  nrepexp,
  gen,
  neg.cost = TRUE
)

Arguments

data.compet	is a matrix for the competition experiment. The first column are the days, the next columns are the counts over time of the plasmid-free colonies (one column per replicated platings), followed by the same number of columns with the total number of colonies picked per replicate, per day.
data.stabexp	is a matrix for the stability experiment. The first column are the days, the next columns are the counts over time of the plasmid-free colonies (one column per replicated platings), followed by the same number of columns with the total number of colonies picked per replicate, per day.
nrc	The number of replicated platings for the competition experiment.
nrepexp	The number of replicated platings for the stability experiment.
gen	Number of generations per day
neg.cost	Logical. If TRUE, then assumes cost is between -1 and 0.
parm=c(beta.o, lam, sig)	which are the initial fraction of plasmid free cells, segregation rate and the plasmid cost. All three parameters must be specified according to the inverse transform of either the 1/(1+e^(-x)) or the -1/(1+e^(-x)) functions.

Value

the negative log-likelihood

Examples

joint.negllSS.flex(parm, data.compet, data.stabexp,nrc,nrepexp, gen,neg.cost=TRUE)

javirudolph/StabilityToolkit documentation built on Jan. 3, 2021, 11:29 p.m.