rsquared,growthrates_fit-method | R Documentation |
Functions to access the results of fitted growthrate objects: summary
,
coef
, rsquared
, deviance
, residuals
,
df.residual
, obs
, results
.
## 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, ...)
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. |
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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