GlobalGrowthFit: 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 for environment="constant"
env_conditions: a list 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)
environment: "dynamic". Always

Usage

# S3 method for GlobalGrowthFit
print(x, ...)
# S3 method for GlobalGrowthFit
coef(object, ...)
# S3 method for GlobalGrowthFit
summary(object, ...)
# S3 method for GlobalGrowthFit
predict(object, env_conditions, times = NULL, ...)
# S3 method for GlobalGrowthFit
residuals(object, ...)
# S3 method for GlobalGrowthFit
vcov(object, ...)
# S3 method for GlobalGrowthFit
deviance(object, ...)
# S3 method for GlobalGrowthFit
fitted(object, ...)
# S3 method for GlobalGrowthFit
logLik(object, ...)
# S3 method for GlobalGrowthFit
AIC(object, ..., k = 2)
# S3 method for 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 GlobalGrowthFit
predictMCMC(
  model,
  times,
  env_conditions,
  niter,
  newpars = NULL,
  formula = . ~ time
)

Value

An instance of MCMCgrowth.

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 NULL (default), no environmental factor is plotted. If set to one character string that matches one entry of x$env_conditions, that condition is plotted in the secondary axis
ylims: A two dimensional vector with the limits of the primary y-axis.
label_x: label of the x-axis
label_y1: Label of the primary y-axis.
label_y2: Label of the secondary y-axis.
line_col: Aesthetic parameter to change the colour of the line geom in the plot, see: ggplot2::geom_line()
line_size: Aesthetic parameter to change the thickness of the line geom in the plot, see: ggplot2::geom_line()
line_type: Aesthetic parameter to change the type of the line geom in the plot, takes numbers (1-6) or strings ("solid") see: ggplot2::geom_line()
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 plot_grid.
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. NULL by default (no new parameters).
formula: A formula stating the column named defining the elapsed time in env_conditions. By default, . ~ time.

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): variance-covariance matrix of the model, estimated as 1/(0.5*Hessian) for regression and as the variance-covariance 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