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GPCERF 0.2.4 (2024-04-09)

Changed

• Dr. Boyu Ren is now the package maintainer.

GPCERF 0.2.3 (2024-03-02)

Changed

• estimate_cerf_nngp takes outcome_col, treatment_col, and covariates_col names as inputs.
• estimate_cerf_gp takes outcome_col, treatment_col, and covariates_col names as inputs.

Added

• estimate_cerf_gp and estimate_cerf_nngp have notes on selecting w.

GPCERF 0.2.2 (2024-02-16)

Changed

• n_thread -> nthread in estimate_noise_nn documentation.

GPCERF 0.2.1 (2023-01-15)

Changed

• full GP –> standard GP
• plots 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

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.