Fitting generalised logistic model to growth data by least squares (using optim function)

Description

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

Usage

1
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.

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