FitMultipleGrowthMCMC: FitMultipleGrowthMCMC class
In biogrowth: Modelling of Population Growth

FitMultipleGrowthMCMC

R Documentation

FitMultipleGrowthMCMC class

Description

The class FitMultipleGrowthMCMC has been superseded by the top-level class GlobalGrowthFit, which provides a unified approach for growth modelling.

Still, it is still returned if the superseded fit_multiple_growth_MCMC() is called.

It is a subclass of list with the items:

fit_results: the object returned by modFit.
best_prediction: a list with the models predictions for each condition.
data: a list with the data used for the fit.
starting: starting values for model fitting
known: parameter values set as known.
sec_models: a named vector with the secondary model for each environmental factor.

Usage

## S3 method for class 'FitMultipleGrowthMCMC'
print(x, ...)

## S3 method for class 'FitMultipleGrowthMCMC'
plot(
  x,
  y = NULL,
  ...,
  add_factor = NULL,
  ylims = NULL,
  label_x = "time",
  label_y1 = "logN",
  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 'FitMultipleGrowthMCMC'
summary(object, ...)

## S3 method for class 'FitMultipleGrowthMCMC'
residuals(object, ...)

## S3 method for class 'FitMultipleGrowthMCMC'
coef(object, ...)

## S3 method for class 'FitMultipleGrowthMCMC'
vcov(object, ...)

## S3 method for class 'FitMultipleGrowthMCMC'
deviance(object, ...)

## S3 method for class 'FitMultipleGrowthMCMC'
fitted(object, ...)

## S3 method for class 'FitMultipleGrowthMCMC'
predict(object, env_conditions, times = NULL, ...)

## S3 method for class 'FitMultipleGrowthMCMC'
logLik(object, ...)

## S3 method for class 'FitMultipleGrowthMCMC'
AIC(object, ..., k = 2)

## S3 method for class 'FitMultipleGrowthMCMC'
predictMCMC(
  model,
  times,
  env_conditions,
  niter,
  newpars = NULL,
  formula = . ~ time
)

Arguments

`x`	an instance of FitMultipleGrowthMCMC.
`...`	ignored
`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`.
`object`	an instance of FitMultipleGrowthMCMC
`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)
`model`	An instance of FitMultipleGrowthMCMC
`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(FitMultipleGrowthMCMC): print of the model
plot(FitMultipleGrowthMCMC): comparison between the model fitted and the data.
summary(FitMultipleGrowthMCMC): statistical summary of the fit.
residuals(FitMultipleGrowthMCMC): 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).
coef(FitMultipleGrowthMCMC): vector of fitted model parameters.
vcov(FitMultipleGrowthMCMC): variance-covariance matrix of the model, estimated as the variance of the samples from the Markov chain.
deviance(FitMultipleGrowthMCMC): deviance of the model, calculated as the sum of squared residuals of the prediction with the lowest standard error.
fitted(FitMultipleGrowthMCMC): fitted values of the model. They are returned as a tibble with 3 columns: time (storage time), exp (experiment identifier) and fitted (fitted value).
predict(FitMultipleGrowthMCMC): model predictions. They are returned as a tibble with 3 columns: time (storage time), logN (observed count), and exp (name of the experiment).
logLik(FitMultipleGrowthMCMC): loglikelihood of the model
AIC(FitMultipleGrowthMCMC): Akaike Information Criterion
predictMCMC(FitMultipleGrowthMCMC): prediction including parameter uncertainty