GlobalGrowthFit: GlobalGrowthFit class
In biogrowth: Modelling of Population Growth

GlobalGrowthFit

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 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 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 `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: `geom_line()`
`line_size`	Aesthetic parameter to change the thickness of the line geom in the plot, see: `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: `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.

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): 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