ModelCompareBase: R6 class ModelCompareBase
In josephsdavid/tswgewrapped: Helpful wrappers for 'tswge', 'vars' and 'nnfor' time series packages
Description
R6 class ModelCompareBase
R6 class ModelCompareBase
Methods
Public methods
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
Method new()
Initialize an object to compare several Univatiate Time Series Models
Usage
ModelCompareBase$new(
data = NA,
mdl_list,
n.ahead = NA,
batch_size = NA,
step_n.ahead = TRUE,
verbose = 0
)
Arguments
dataThe dataframe containing the time series realizations (data should not contain time index)
mdl_listA named list of all models (see format below)
n.aheadThe number of observations used to calculate ASE or forecast ahead
batch_sizeIf any of the models used sliding ase method,
then this number indicates the batch size to use
step_n.aheadIf using sliding window, should batches be incremented by n.ahead
(Default = TRUE)
verboseHow much to print during the model building and other processes (Default = 0)
Returns
A new 'ModelCompareBase' object.
Method get_data()
Returns the time series realization
Usage
ModelCompareBase$get_data()
Returns
The Time Series Realization
Method get_data_var_interest()
Returns the dependent variable data only
Usage
ModelCompareBase$get_data_var_interest()
Returns
The dependent variable data only
Method get_batch_size()
Returns the batch size value
Usage
ModelCompareBase$get_batch_size()
Returns
The Batch Size Value
Method set_batch_size()
Sets the batch size value
Usage
ModelCompareBase$set_batch_size(batch_size)
Arguments
batch_sizeBatch Size Value
Method get_n.ahead()
Returns the n.ahead value
Usage
ModelCompareBase$get_n.ahead()
Returns
The n.ahead value
Method set_verbose()
Adjust the verbosity level
Usage
ModelCompareBase$set_verbose(verbose = 0)
Arguments
verbose0 = Minimal Printing only (usualy limited to step being performed)
1 = Basic printing of model builds, etc.
2 = Reserved for debugging mode. May slow down the run due to excessive printing, especially when using batches
Method get_model_names()
Get all the model names
Usage
ModelCompareBase$get_model_names(only_sliding = FALSE)
Arguments
only_slidingIf TRUE, this will only plot the ASEs for
the models that used window ASE calculations
Returns
A vector of all model names
Method add_models()
Add models to the existing object
Usage
ModelCompareBase$add_models(mdl_list, batch_size = -1)
Arguments
mdl_listThe list of new models to add
batch_sizeThe batch size to use if model is using sliding ASE calculations
Method remove_models()
Remove models from the object
Usage
ModelCompareBase$remove_models(mdl_names)
Arguments
mdl_namesA vector of the model names to remove.
Method keep_models()
Keep only the provided models
Usage
ModelCompareBase$keep_models(mdl_names)
Arguments
mdl_namesA vector of the model names to keep.
Method compute_metrics()
Computes the Metrics for the models
Usage
ModelCompareBase$compute_metrics(step_n.ahead = TRUE)
Arguments
step_n.aheadIf TRUE, for rolling window calculations, the step size
will be equal to n.ahead, else it will be equal to 1
Method plot_simple_forecasts()
Plots the simple forecast for each model
Usage
ModelCompareBase$plot_simple_forecasts(
lastn = FALSE,
newxreg = NA,
limits = FALSE,
zoom = NA,
plot = TRUE
)
Arguments
lastnIf TRUE, this will plot the forecasts forthe last n.ahead values of the realization (Default: FALSE)
newxregThe future exogenous variable values. Applicable to models that require the values of the new exogenous variables to be provided for future forecasts, e.g. nnfor::mlp()
limitsIf TRUE, this will also plot the lower and upper limits of the forecasts (Default: FALSE)
zoomA number indicating how much to zoom into the plot.
For example zoom = 50 will only plot the last 50 points of the realization
Useful for cases where realizations that are long and n.ahead is small.
plotIf FALSE the plots are not plotted; useful when you want to just return the data (Default = TRUE)
Method plot_batch_forecasts()
Plots the forecasts per batch for all models
Usage
ModelCompareBase$plot_batch_forecasts(
only_sliding = TRUE,
plot = TRUE,
silent = FALSE
)
Arguments
only_slidingIf TRUE, this will only plot the batch forecasts
for the models that used window ASE calculations
plotIf FALSE the plots are not plotted; useful when you want to just return the data (Default = TRUE)
silentIf FALSE, any warnings are suppressed
Method plot_batch_ases()
Plots the ASEs per batch for all models
Usage
ModelCompareBase$plot_batch_ases(
only_sliding = TRUE,
plot = TRUE,
silent = FALSE
)
Arguments
only_slidingIf TRUE, this will only plot the ASEs for
the models that used window ASE calculations
plotIf FALSE the plots are not plotted; useful when you want to just return the data (Default = TRUE)
silentIf FALSE, any warnings are suppressed
Method plot_boxplot_ases()
Plots the boxplot of the ASE values for the models
Usage
ModelCompareBase$plot_boxplot_ases(plot = TRUE)
Arguments
plotIf FALSE the plots are not plotted; useful when you want to just return the data (Default = TRUE)
Method statistical_compare()
Statistically compares the ASE values of the models using
ANOVA and Tukey Adjustment for multiple comparison
Usage
ModelCompareBase$statistical_compare()
Returns
The results of the ANOVA test
Method get_tabular_metrics()
Gets the metrics and results in tabular format
Usage
ModelCompareBase$get_tabular_metrics(only_sliding = FALSE, ases = TRUE)
Arguments
only_slidingIf TRUE, this will only get results for models that use a
sliding ASE calculation method. (Default: FALSE)
asesIf TRUE returns the ASE values for each batch. If FALSE returns the
forecasts, and the lower and upper limits asscoiated with the forecasts
Method summarize_build()
Returns the model Build Summary (if applicable)
Usage
ModelCompareBase$summarize_build()
josephsdavid/tswgewrapped documentation built on July 31, 2020, 9:36 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description
R6 class ModelCompareBase
R6 class ModelCompareBase
Methods
Public methods
Method new()
Initialize an object to compare several Univatiate Time Series Models
Usage
ModelCompareBase$new( data = NA, mdl_list, n.ahead = NA, batch_size = NA, step_n.ahead = TRUE, verbose = 0 )
Arguments
dataThe dataframe containing the time series realizations (data should not contain time index)
mdl_listA named list of all models (see format below)
n.aheadThe number of observations used to calculate ASE or forecast ahead
batch_sizeIf any of the models used sliding ase method, then this number indicates the batch size to use
step_n.aheadIf using sliding window, should batches be incremented by n.ahead (Default = TRUE)
verboseHow much to print during the model building and other processes (Default = 0)
Returns
A new 'ModelCompareBase' object.
Method get_data()
Returns the time series realization
Usage
ModelCompareBase$get_data()
Returns
The Time Series Realization
Method get_data_var_interest()
Returns the dependent variable data only
Usage
ModelCompareBase$get_data_var_interest()
Returns
The dependent variable data only
Method get_batch_size()
Returns the batch size value
Usage
ModelCompareBase$get_batch_size()
Returns
The Batch Size Value
Method set_batch_size()
Sets the batch size value
Usage
ModelCompareBase$set_batch_size(batch_size)
Arguments
batch_sizeBatch Size Value
Method get_n.ahead()
Returns the n.ahead value
Usage
ModelCompareBase$get_n.ahead()
Returns
The n.ahead value
Method set_verbose()
Adjust the verbosity level
Usage
ModelCompareBase$set_verbose(verbose = 0)
Arguments
verbose0 = Minimal Printing only (usualy limited to step being performed) 1 = Basic printing of model builds, etc. 2 = Reserved for debugging mode. May slow down the run due to excessive printing, especially when using batches
Method get_model_names()
Get all the model names
Usage
ModelCompareBase$get_model_names(only_sliding = FALSE)
Arguments
only_slidingIf TRUE, this will only plot the ASEs for the models that used window ASE calculations
Returns
A vector of all model names
Method add_models()
Add models to the existing object
Usage
ModelCompareBase$add_models(mdl_list, batch_size = -1)
Arguments
mdl_listThe list of new models to add
batch_sizeThe batch size to use if model is using sliding ASE calculations
Method remove_models()
Remove models from the object
Usage
ModelCompareBase$remove_models(mdl_names)
Arguments
mdl_namesA vector of the model names to remove.
Method keep_models()
Keep only the provided models
Usage
ModelCompareBase$keep_models(mdl_names)
Arguments
mdl_namesA vector of the model names to keep.
Method compute_metrics()
Computes the Metrics for the models
Usage
ModelCompareBase$compute_metrics(step_n.ahead = TRUE)
Arguments
step_n.aheadIf TRUE, for rolling window calculations, the step size will be equal to n.ahead, else it will be equal to 1
Method plot_simple_forecasts()
Plots the simple forecast for each model
Usage
ModelCompareBase$plot_simple_forecasts( lastn = FALSE, newxreg = NA, limits = FALSE, zoom = NA, plot = TRUE )
Arguments
lastnIf TRUE, this will plot the forecasts forthe last n.ahead values of the realization (Default: FALSE)
newxregThe future exogenous variable values. Applicable to models that require the values of the new exogenous variables to be provided for future forecasts, e.g. nnfor::mlp()
limitsIf TRUE, this will also plot the lower and upper limits of the forecasts (Default: FALSE)
zoomA number indicating how much to zoom into the plot. For example zoom = 50 will only plot the last 50 points of the realization Useful for cases where realizations that are long and n.ahead is small.
plotIf FALSE the plots are not plotted; useful when you want to just return the data (Default = TRUE)
Method plot_batch_forecasts()
Plots the forecasts per batch for all models
Usage
ModelCompareBase$plot_batch_forecasts( only_sliding = TRUE, plot = TRUE, silent = FALSE )
Arguments
only_slidingIf TRUE, this will only plot the batch forecasts for the models that used window ASE calculations
plotIf FALSE the plots are not plotted; useful when you want to just return the data (Default = TRUE)
silentIf FALSE, any warnings are suppressed
Method plot_batch_ases()
Plots the ASEs per batch for all models
Usage
ModelCompareBase$plot_batch_ases( only_sliding = TRUE, plot = TRUE, silent = FALSE )
Arguments
only_slidingIf TRUE, this will only plot the ASEs for the models that used window ASE calculations
plotIf FALSE the plots are not plotted; useful when you want to just return the data (Default = TRUE)
silentIf FALSE, any warnings are suppressed
Method plot_boxplot_ases()
Plots the boxplot of the ASE values for the models
Usage
ModelCompareBase$plot_boxplot_ases(plot = TRUE)
Arguments
plotIf FALSE the plots are not plotted; useful when you want to just return the data (Default = TRUE)
Method statistical_compare()
Statistically compares the ASE values of the models using ANOVA and Tukey Adjustment for multiple comparison
Usage
ModelCompareBase$statistical_compare()
Returns
The results of the ANOVA test
Method get_tabular_metrics()
Gets the metrics and results in tabular format
Usage
ModelCompareBase$get_tabular_metrics(only_sliding = FALSE, ases = TRUE)
Arguments
only_slidingIf TRUE, this will only get results for models that use a sliding ASE calculation method. (Default: FALSE)
asesIf TRUE returns the ASE values for each batch. If FALSE returns the forecasts, and the lower and upper limits asscoiated with the forecasts
Method summarize_build()
Returns the model Build Summary (if applicable)
Usage
ModelCompareBase$summarize_build()
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.