datafit: Fitting generalised logistic model to growth data by least...

In qfa: Tools for Quantitative Fitness Analysis (QFA) of Arrayed Microbial Cultures Growing on Solid Agar Surfaces

Description

Uses the optim function to carry out least squares fit of logistic model to growth data.

Usage

data.fit(tim,growth,inocguess,xybounds,inits=list(),logTransform=FALSE,verbose=FALSE)

Arguments

tim	Vector of culture size observation times
growth	Vector of observed culture sizes
inocguess	Inocluation density estimate (same physical units as growth vector)
xybounds	List of upper and lower bounds for model parameters. NEED TO ADD EXAMPLE OF CONTENTS.
inits	List of initial guesses for each parameter. If empty list, generate initial guesses from mean of bounds
logTransform	Boolean specifying whether we shoudl carry out model fit on log scale.
verbose	Boolean specifying level of reporting during model fitting

Value

A named vector of best parameter estimates along with the objective function (square distance between data and model) at the solution.

qfa documentation built on Feb. 22, 2020, 3:01 a.m.