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growthrates (version 0.8.4)

rsquared,growthrates_fit-method: 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 growthrates_fit
rsquared(object, ...)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

# S4 method for 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

Run this code

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])


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