# GPCERF 0.2.1 (2023-01-15)

## Changed
- `full GP` --> `standard GP`
- `plot`s of exposure response function objects include covariate balance.
- `formula` is no longer need in nn functions.
- `estimate_gps` now returns the used exposure level, too. 
- `train_gps` --> `estimate_gps` 
- The nearest neighbor approach does not get `expand` as an input parameter (`n_neighbor` * `expand` --> `n_neighbor`).
- The weighted covariate balance now is computed using the wCorr package.


# GPCERF 0.2.0 (2023-01-22)

## Changed
* estimate_noise_nn now allows for parallelization with an added argument `nthread` for the number of CPUs used in parallel.
* estimate_mean_sd_nn now only computes the posterior variance.
* find_optimal_nn now returns the posterior mean and covariate balance for the optimal hyper-parameter values.
* Add an argument kernel_fn to all nn related functions to allow for user-defined kernel functions.
* Add an argument formula to all nn related functions to allow for user-defined design matrix.
* find_optimal_nn becomes an internal function.
* estimate_noise_gp and estimate_noise_nn become internal functions. 
* estimate_mean_sd_nn becomes an internal function.
* compute_weight_gp becomes an internal function.
* compute_w_corr accepts w and confounders separately. It also normalizes w internally.  
* compute_posterior_sd_nn becomes an internal function.
* compute_posterior_m_nn becomes an internal function.
* compute_derive_weights_gp becomes an internal function. 
* compute_m_sigma becomes an internal function.
* compute_inverse becomes an internal function. 
* In compute_m_sigma, tuning option does not have a default value. 
* train_gps does not have default values.
* train_gps accepts vector of the SuperLearner package's libraries.
* train_GPS -> train_gps


# GPCERF 0.1.0 (2022-07-02)

## Changed

* nn_cp_calc -> compute_rl_deriv_nn
* deriv_nn_fast -> compute_deriv_nn
* get_nn_sd -> compute_posterior_sd_nn
* nn_sigma_est -> estimate_noise_nn
* idx.all -> idx_select
* GPS.new -> GPS_w
* w.new -> w
* get.nn.fast -> compute_posterior_m_nn
* w.est -> w 
* nn_balance -> best_nn_cb

## Added

* Package website using pkgdown
* Logger functions
* compute_sd_gp function


# GPCERF 0.0.1 (2022-03-31)

## Changed

* Removed examples from internal functions
* w.obs -> w_obs
* inv.Sigma.obs -> inv_sigma_obs
* obs.use -> scaled_obs
* tune.fn -> compute_m_sigma
* GP.weights.test -> compute_weight_gp
* data.generate -> generate_synthetic_data 


## Added

* estimate_noise function
* estimate_cerf_gp function
* compute_inverse function
* compute_w_corr function
