# ldmppr 1.1.1

* Updated the workflow pipeline to allow passage of S3 class objects between functions to simplify the user experience.
The four main steps of the workflow (fit process model, train mark model, check model fit, simulate realizations) now each have their own S3 class and associated methods and you can pass the
objects forward between functions. See the updated documentation for details.

# ldmppr 1.1.0

* 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.

# ldmppr 1.0.4

* 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.

# ldmppr 1.0.3

# ldmppr 1.0.2

# ldmppr 1.0.1

# ldmppr 1.0.0

# ldmppr 0.1.0

* Initial CRAN submission.
