FitDynamicGrowthMCMC {biogrowth} R Documentation

## FitDynamicGrowthMCMC class

### Description

The class FitDynamicGrowthMCMC has been superseded by the top-level class GrowthFit, which provides a unified approach for growth modelling.

Still, it is returned if the superseded fit_MCMC_growth() is called.

It is a subclass of list with the items:

• fit_results: the object returned by modMCMC.

• best_prediction: the model prediction for the fitted parameters.

• env_conditions: environmental conditions for the fit.

• data: 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 'FitDynamicGrowthMCMC'
print(x, ...)

## S3 method for class 'FitDynamicGrowthMCMC'
plot(
x,
y = NULL,
...,
ylims = NULL,
label_y1 = "logN",
line_col = "black",
line_size = 1,
line_type = 1,
point_col = "black",
point_size = 3,
point_shape = 16,
line_col2 = "black",
line_size2 = 1,
line_type2 = "dashed"
)

## S3 method for class 'FitDynamicGrowthMCMC'
summary(object, ...)

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

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

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

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

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

## S3 method for class 'FitDynamicGrowthMCMC'
predict(object, times = NULL, newdata = NULL, ...)

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

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

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


### Arguments

 x The object of class FitDynamicGrowthMCMC to plot. ... ignored y ignored add_factor whether to plot also one environmental factor. If NULL (default), no environmenta 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_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() point_col Aesthetic parameter to change the colour of the point geom, see: geom_point() point_size Aesthetic parameter to change the size of the point geom, see: geom_point() point_shape Aesthetic parameter to change the shape of the point geom, see: geom_point() 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. object an instance of FitDynamicGrowthMCMC times Numeric vector of storage times for the predictions. newdata a tibble describing the environmental conditions (as env_conditions) in predict_dynamic_growth(). If NULL (default), uses the same conditions as those for fitting. k penalty for the parameters (k=2 by default) model An instance of FitDynamicGrowthMCMC 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. 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(FitDynamicGrowthMCMC): print of the model

• plot(FitDynamicGrowthMCMC): compares the model fitted against the data.

• summary(FitDynamicGrowthMCMC): statistical summary of the fit.

• residuals(FitDynamicGrowthMCMC): model residuals.

• coef(FitDynamicGrowthMCMC): vector of fitted model parameters.

• vcov(FitDynamicGrowthMCMC): variance-covariance matrix of the model, estimated as the variance of the samples from the Markov chain.

• deviance(FitDynamicGrowthMCMC): deviance of the model, calculated as the sum of squared residuals for the parameter values resulting in the best fit.

• fitted(FitDynamicGrowthMCMC): vector of fitted values.

• predict(FitDynamicGrowthMCMC): vector of model predictions.

• logLik(FitDynamicGrowthMCMC): loglikelihood of the model

• AIC(FitDynamicGrowthMCMC): Akaike Information Criterion

• predictMCMC(FitDynamicGrowthMCMC): prediction including parameter uncertainty

[Package biogrowth version 1.0.1 Index]