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@Naeemkh Naeemkh released this 22 Jan 14:53
· 187 commits to main since this release
v0.2.0
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Learn about vigilant mode.
  • 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
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