The DiseasyModelGLM module implements common structure and functionality to
GLM regression class of models beyond the model structure provided by DiseasyModelRegression.
Most notably, the model module implements the $fit_regression() and $get_prediction() methods using
GLM.
diseasy includes two simple models that uses the DiseasyModelGLM module:
DiseasyModelG0 and DiseasyModelG1
These models implements a constant predictor and a exponential model based on the previous 7 and 21 days
of observations, respectively.
When making a custom GLM model, the subclass should implement the $update_formula() method.
The $update_formula() method should update the formula based on the stratifications.
If the model should flexibly adapt to different stratifications, this method should be implemented.
See DiseasyModelG0 and DiseasyModelG1 for
examples of how this can be done.
Value
A new instance of the DiseasyModelGLM, DiseasyModelG0 or
DiseasyModelG1 R6 class.
Super classes
DiseasyBaseModule -> DiseasyModel -> DiseasyModelRegression -> DiseasyModelBRM
Methods
DiseasyModelBRM$new()
Creates a new instance of the DiseasyModelBRM R6 class.
This module is typically not constructed directly but rather through DiseasyModelB* classes,
such as DiseasyModelB0 and DiseasyModelB1.
Usage
DiseasyModelBRM$new(...)Arguments
...parameters sent to
DiseasyModelRegressionR6 constructor.
Details
Helper class for the the DiseasyModelB* R6 classes.
Returns
A new instance of the DiseasyModelBRM R6 class.
Super classes
DiseasyBaseModule -> DiseasyModel -> DiseasyModelRegression -> DiseasyModelBRM -> DiseasyModelB_ -> DiseasyModelB0
Methods
DiseasyModelB0$new()
Usage
DiseasyModelB0$new(parameters = NULL, ...)Arguments
parameters(
named list())
List of parameters to set for the model during initialization.
Parameters controlling the dynamics of the model:
*season.scale(numeric(1))
Sets the scale of the season model. The scale is the percent wise difference between most active and least active period. IfNULL(default), the default value of the season module is used.
*season.peak(numeric(1))
Sets the period of maximal activity (days past new-year). By default, risk of infection is in antiphase with the DMI climate normal of the maximum daily temperature (for Denmark). IfNULL(default), the default value of the season module is used.
Additional parameters are: (named list())
List of parameters to set for the model during initialization.
Each model has their own parameters.
Common parameters are:
*training_length(named numeric(3))
The number of days that should be included in the training splits of the data for the model. Allowed splits are: "training", "testing", and "validation"....parameters sent to
DiseasyModelB_R6 constructor
Returns
A new instance of the DiseasyModelB0 R6 class.
Super classes
DiseasyBaseModule -> DiseasyModel -> DiseasyModelRegression -> DiseasyModelBRM -> DiseasyModelB_ -> DiseasyModelB1
Methods
DiseasyModelB1$new()
Usage
DiseasyModelB1$new(parameters = NULL, ...)Arguments
parameters(
named list())
List of parameters to set for the model during initialization.
Parameters controlling the dynamics of the model:
*season.scale(numeric(1))
Sets the scale of the season model. The scale is the percent wise difference between most active and least active period. IfNULL(default), the default value of the season module is used.
*season.peak(numeric(1))
Sets the period of maximal activity (days past new-year). By default, risk of infection is in antiphase with the DMI climate normal of the maximum daily temperature (for Denmark). IfNULL(default), the default value of the season module is used.
Additional parameters are: (named list())
List of parameters to set for the model during initialization.
Each model has their own parameters.
Common parameters are:
*training_length(named numeric(3))
The number of days that should be included in the training splits of the data for the model. Allowed splits are: "training", "testing", and "validation"....parameters sent to
DiseasyModelB_R6 constructor
Returns
A new instance of the DiseasyModelB1 R6 class.
Examples
model <- DiseasyModelG0$new()
rm(model)
