GrowthFit  R Documentation 
The GrowthFit
class contains a growth model fitted to data under
static or dynamic conditions. Its constructor is fit_growth()
.
It is a subclass of list with the items:
environment: type of environment as in fit_growth()
algorithm: type of algorithm as in fit_growth()
data: data used for model fitting
start: initial guess of the model parameters
known: fixed model parameters
primary_model: a character describing the primary model
fit_results: an instance of modFit or modMCMC with the results of the fit
best_prediction: Instance of GrowthPrediction with the best growth fit
sec_models: a named vector with the secondary models assigned for each
environmental factor. NULL
for environment="constant"
env_conditions: a tibble with the environmental conditions used for model
fitting. NULL
for environment="constant"
niter: number of iterations of the Markov chain. NULL
if algorithm != "MCMC"
logbase_mu: base of the logarithm for the definition of parameter mu (check the relevant vignette)
logbase_logN: base of the logarithm for the definition of the population size (check the relevant vignette)
## S3 method for class 'GrowthFit'
print(x, ...)
## S3 method for class 'GrowthFit'
coef(object, ...)
## S3 method for class 'GrowthFit'
summary(object, ...)
## S3 method for class 'GrowthFit'
predict(object, times = NULL, env_conditions = NULL, ...)
## S3 method for class 'GrowthFit'
residuals(object, ...)
## S3 method for class 'GrowthFit'
vcov(object, ...)
## S3 method for class 'GrowthFit'
deviance(object, ...)
## S3 method for class 'GrowthFit'
fitted(object, ...)
## S3 method for class 'GrowthFit'
logLik(object, ...)
## S3 method for class 'GrowthFit'
AIC(object, ..., k = 2)
## S3 method for class 'GrowthFit'
plot(
x,
y = NULL,
...,
add_factor = NULL,
line_col = "black",
line_size = 1,
line_type = 1,
point_col = "black",
point_size = 3,
point_shape = 16,
ylims = NULL,
label_y1 = NULL,
label_y2 = add_factor,
label_x = "time",
line_col2 = "black",
line_size2 = 1,
line_type2 = "dashed"
)
## S3 method for class 'GrowthFit'
predictMCMC(
model,
times,
env_conditions,
niter,
newpars = NULL,
formula = . ~ time
)
x 
The object of class GrowthFit to plot. 
... 
ignored. 
object 
an instance of GrowthFit 
times 
Numeric vector of storage times for the predictions. 
env_conditions 
Tibble with the (dynamic) environmental conditions during the experiment. It must have one column named 'time' with the storage time and as many columns as required with the environmental conditions. 
k 
penalty for the parameters (k=2 by default) 
y 
ignored 
add_factor 
whether to plot also one environmental factor.
If 
line_col 
Aesthetic parameter to change the colour of the line geom in the plot, see: 
line_size 
Aesthetic parameter to change the thickness of the line geom in the plot, see: 
line_type 
Aesthetic parameter to change the type of the line geom in the plot, takes numbers (16) or strings ("solid") see: 
point_col 
Aesthetic parameter to change the colour of the point geom, see: 
point_size 
Aesthetic parameter to change the size of the point geom, see: 
point_shape 
Aesthetic parameter to change the shape of the point geom, see: 
ylims 
A two dimensional vector with the limits of the primary yaxis.

label_y1 
Label of the primary yaxis. 
label_y2 
Label of the secondary yaxis. Ignored if 
label_x 
Label of the xaxis 
line_col2 
Same as lin_col, but for the environmental factor. Ignored if 
line_size2 
Same as line_size, but for the environmental factor. Ignored if 
line_type2 
Same as lin_type, but for the environmental factor. Ignored if 
model 
An instance of GrowthFit 
niter 
Number of iterations. 
newpars 
A named list defining new values for the some model parameters.
The name must be the identifier of a model already included in the model.
These parameters do not include variation, so defining a new value for a fitted
parameters "fixes" it. 
formula 
A formula stating the column named defining the elapsed time in

An instance of MCMCgrowth.
print(GrowthFit)
: print of the model
coef(GrowthFit)
: vector of fitted model parameters.
summary(GrowthFit)
: statistical summary of the fit.
predict(GrowthFit)
: vector of model predictions.
residuals(GrowthFit)
: vector of model residuals.
vcov(GrowthFit)
: variancecovariance matrix of the model, estimated
as 1/(0.5*Hessian) for regression and as the variancecovariance of the draws
for MCMC
deviance(GrowthFit)
: deviance of the model.
fitted(GrowthFit)
: vector of fitted values.
logLik(GrowthFit)
: loglikelihood of the model
AIC(GrowthFit)
: Akaike Information Criterion
plot(GrowthFit)
: compares the fitted model against the data.
predictMCMC(GrowthFit)
: prediction including parameter uncertainty
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