rsquared,growthrates_fit-method {growthrates}

Accessor Methods of Package growthrates.

Description

Functions to access the results of fitted growthrate objects: summary, coef, rsquared, deviance, residuals, df.residual, obs, results.

Usage

## S4 method for signature 'growthrates_fit'
rsquared(object, ...)

## S4 method for signature 'growthrates_fit'
obs(object, ...)

## S4 method for signature 'growthrates_fit'
coef(object, extended = FALSE, ...)

## S4 method for signature 'easylinear_fit'
coef(object, ...)

## S4 method for signature 'smooth.spline_fit'
coef(object, extended = FALSE, ...)

## S4 method for signature 'growthrates_fit'
deviance(object, ...)

## S4 method for signature 'growthrates_fit'
summary(object, ...)

## S4 method for signature 'nonlinear_fit'
summary(object, cov = TRUE, ...)

## S4 method for signature 'growthrates_fit'
residuals(object, ...)

## S4 method for signature 'growthrates_fit'
df.residual(object, ...)

## S4 method for signature 'smooth.spline_fit'
summary(object, cov = TRUE, ...)

## S4 method for signature 'smooth.spline_fit'
df.residual(object, ...)

## S4 method for signature 'smooth.spline_fit'
deviance(object, ...)

## S4 method for signature 'multiple_fits'
coef(object, ...)

## S4 method for signature 'multiple_fits'
rsquared(object, ...)

## S4 method for signature 'multiple_fits'
deviance(object, ...)

## S4 method for signature 'multiple_fits'
results(object, ...)

## S4 method for signature 'multiple_easylinear_fits'
results(object, ...)

## S4 method for signature 'multiple_fits'
summary(object, ...)

## S4 method for signature 'multiple_fits'
residuals(object, ...)

Arguments

object

name of a 'growthrate' object.

...

other arguments passed to the methods.

extended

boolean if extended set of parameters shoild be printed

cov

boolean if the covariance matrix should be printed.

Examples

data(bactgrowth)
splitted.data <- multisplit(bactgrowth, c("strain", "conc", "replicate"))

## get table from single experiment
dat <- splitted.data[[10]]

fit1 <- fit_spline(dat$time, dat$value, spar=0.5)
coef(fit1)
summary(fit1)

## derive start parameters from spline fit
p <- c(coef(fit1), K = max(dat$value))
fit2 <- fit_growthmodel(grow_logistic, p=p, time=dat$time, y=dat$value, transform="log")
coef(fit2)
rsquared(fit2)
deviance(fit2)

summary(fit2)

plot(residuals(fit2) ~ obs(fit2)[,2])