FitMultipleGrowthMCMC {biogrowth} | 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The class FitMultipleGrowthMCMC has been superseded by the top-level class GlobalGrowthFit, which provides a unified approach for growth modelling.
Still, it is still returned if the superseded fit_multiple_growth_MCMC()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 |
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: |
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: |
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 |
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. |
formula |
A formula stating the column named defining the elapsed time in
|
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