v0.4.0

Changed

• Docker image supports R 4.2.3
• generate_syn_data supports vectorized_y to accelerate data generation.
• matching_fun --> dist_measure
• matching_l1 --> matching_fn
• estimate_semipmetric_erf now takes the gam models optional arguments.
• estimate_pmetric_erf now takes the gnm models optional arguments.
• trim_quantiles --> exposure_trim_qtls
• generate_pseudo_pop function accepts gps_obj as an optional input.
• internal_use is not part of parameters for estimate_gps function.
• estimate_gps function only returns id, w, and computed gps as part of dataset.
• Now the design and analysis phases are explicitly separated.
• gps_model --> gps_density. Now it takes, normal and kernel options instead of parametric and non-parametric options.

Added

• estimate_npmetric_erf supports both locpol and KernSmooth approaches.
• There is gps_trim_qtls input parameter to trim data samples based on gps values.
• Now users can also collect the original data in the pseudo population object.

Fixed

• A bug with swapping transformed covairates with original one.