GlobalGrowthFit {biogrowth}  R Documentation 
GlobalGrowthFit class
Description
The GlobalGrowthFit
class contains a growth model fitted to data
using a global approach. Its constructor is fit_growth()
.
It is a subclass of list with the items:
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
forenvironment="constant"
env_conditions: a list with the environmental conditions used for model fitting.
NULL
forenvironment="constant"
niter: number of iterations of the Markov chain.
NULL
ifalgorithm != "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)
environment: "dynamic". Always
Usage
## S3 method for class 'GlobalGrowthFit'
print(x, ...)
## S3 method for class 'GlobalGrowthFit'
coef(object, ...)
## S3 method for class 'GlobalGrowthFit'
summary(object, ...)
## S3 method for class 'GlobalGrowthFit'
predict(object, env_conditions, times = NULL, ...)
## S3 method for class 'GlobalGrowthFit'
residuals(object, ...)
## S3 method for class 'GlobalGrowthFit'
vcov(object, ...)
## S3 method for class 'GlobalGrowthFit'
deviance(object, ...)
## S3 method for class 'GlobalGrowthFit'
fitted(object, ...)
## S3 method for class 'GlobalGrowthFit'
logLik(object, ...)
## S3 method for class 'GlobalGrowthFit'
AIC(object, ..., k = 2)
## S3 method for class 'GlobalGrowthFit'
plot(
x,
y = NULL,
...,
add_factor = NULL,
ylims = NULL,
label_x = "time",
label_y1 = NULL,
label_y2 = add_factor,
line_col = "black",
line_size = 1,
line_type = "solid",
line_col2 = "black",
line_size2 = 1,
line_type2 = "dashed",
point_size = 3,
point_shape = 16,
subplot_labels = "AUTO"
)
## S3 method for class 'GlobalGrowthFit'
predictMCMC(
model,
times,
env_conditions,
niter,
newpars = NULL,
formula = . ~ time
)
Arguments
x 
an instance of GlobalGrowthFit 
... 
ignored 
object 
an instance of GlobalGrowthFit 
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. 
times 
Numeric vector of storage times for the predictions. 
k 
penalty for the parameters (k=2 by default) 
y 
ignored 
add_factor 
whether to plot also one environmental factor.
If 
ylims 
A two dimensional vector with the limits of the primary yaxis. 
label_x 
label of the xaxis 
label_y1 
Label of the primary yaxis. 
label_y2 
Label of the secondary yaxis. 
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: 
line_col2 
Same as lin_col, but for the environmental factor. 
line_size2 
Same as line_size, but for the environmental factor. 
line_type2 
Same as lin_type, but for the environmental factor. 
point_size 
Size of the data points 
point_shape 
shape of the data points 
subplot_labels 
labels of the subplots according to 
model 
An instance of GlobalGrowthFit 
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

Value
An instance of MCMCgrowth.
Methods (by generic)

print(GlobalGrowthFit)
: print of the model 
coef(GlobalGrowthFit)
: vector of fitted model parameters. 
summary(GlobalGrowthFit)
: statistical summary of the fit. 
predict(GlobalGrowthFit)
: vector of model predictions 
residuals(GlobalGrowthFit)
: model residuals. They are returned as a tibble with 4 columns: time (storage time), logN (observed count), exp (name of the experiment) and res (residual). 
vcov(GlobalGrowthFit)
: variancecovariance matrix of the model, estimated as 1/(0.5*Hessian) for regression and as the variancecovariance of the draws for MCMC 
deviance(GlobalGrowthFit)
: deviance of the model. 
fitted(GlobalGrowthFit)
: fitted values. They are returned as a tibble with 3 columns: time (storage time), exp (experiment identifier) and fitted (fitted value). 
logLik(GlobalGrowthFit)
: loglikelihood of the model 
AIC(GlobalGrowthFit)
: Akaike Information Criterion 
plot(GlobalGrowthFit)
: comparison between the fitted model and the experimental data. 
predictMCMC(GlobalGrowthFit)
: prediction including parameter uncertainty