all_easylinear {growthrates}

Easy Growth Rates Fit to data Frame

Description

Determine maximum growth rates from log-linear part of the growth curve for a series of experiments.

Usage

all_easylinear(...)

## S3 method for class 'formula'
all_easylinear(formula, data, h = 5, quota = 0.95, subset = NULL, ...)

## S3 method for class 'data.frame'
all_easylinear(
  data,
  grouping,
  time = "time",
  y = "value",
  h = 5,
  quota = 0.95,
  ...
)

Arguments

...

generic parameters, reserved for future extensions.

formula

model formula specifying dependent, independent and grouping variables in the form: dependent ~ independent | group1 + group2 + ....

data

data frame of observational data.

h

with of the window (number of data).

quota

part of window fits considered for the overall linear fit (relative to max. growth rate).

subset

a specification of the rows to be used: defaults to all rows.

grouping

model formula or character vector of criteria defining subsets in the data frame.

time

character vectors with name independent variabl.e.

y

character vector with name of dependent variable

Value

object with parameters of all fits.

References

Hall, BG., Acar, H, Nandipati, A and Barlow, M (2014) Growth Rates Made Easy. Mol. Biol. Evol. 31: 232-38, doi:10.1093/molbev/mst187

See Also

Other fitting functions: all_growthmodels(), all_splines(), fit_easylinear(), fit_growthmodel(), fit_spline()

Examples

library("growthrates")
L <- all_easylinear(value ~ time | strain + conc + replicate, data=bactgrowth)
summary(L)
coef(L)
rsquared(L)

results <- results(L)

library(lattice)
xyplot(mumax ~ conc|strain, data=results)