Introduced S3 classes and associated methods for the 4 main workflow steps (fit process model/train mark model/check model fit/simulate realizations).
Replaced the estimate_parameters_sc() and
estimate_parameters_sc_parallel() functions with the
unified estimate_process_parameters() function. We
redesigned this function to provide multiple strategies for the
optimization procedure and refactored the underlying C++ code to improve
efficiency.
Removed explicit dependence on the Bundle package and introduced
the save_mark_model() and load_mark_model()
functions to handle saving and loading trained mark models.
Updated the small example dataset and example trained mark model to reflect changes in the package functions.
updated train_mark_model() and
check_model_fit() and simulate_mpp() to
include scaled_rasters argument to determine if scaling
needs to be performed.
added a new example dataset entitled
medium_example_data and corresponding raster
files.
updated the plot_mpp() function to use the operator
%>% instead of the |> operator to ensure
compatibility with older versions of R.