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The class FitDynamicGrowthMCMC has been superseded by the top-level class GrowthFit, which provides a unified approach for growth modelling.
Still, it is returned if the superseded fit_MCMC_growth()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,
...,
add_factor = NULL,
ylims = NULL,
label_y1 = "logN",
label_y2 = add_factor,
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 |
... |
ignored |
y |
ignored |
add_factor |
whether to plot also one environmental factor.
If |
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: |
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 (1-6) or strings ("solid") see: |
point_col |
Aesthetic parameter to change the colour of the point geom, see: |
point_size |
Aesthetic parameter to change the size of the point geom, see: |
point_shape |
Aesthetic parameter to change the shape of the point geom, 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. |
object |
an instance of FitDynamicGrowthMCMC |
times |
Numeric vector of storage times for the predictions. |
newdata |
a tibble describing the environmental conditions (as |
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. |
formula |
A formula stating the column named defining the elapsed time in
|
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