add_aspre_interactions |
Add interaction terms corresponding to ASPRE model |
aspre |
Computes ASPRE score |
aspre_emulation |
Emulation-based OHS estimation for ASPRE |
aspre_k2 |
Cost estimating function in ASPRE simulation |
aspre_parametric |
Parametric-based OHS estimation for ASPRE |
ci_cover_a_yn |
Data for example on asymptotic confidence interval for OHS. |
ci_cover_cost_a_yn |
Data for example on asymptotic confidence interval for min cost. |
ci_cover_cost_e_yn |
Data for example on empirical confidence interval for min cost. |
ci_cover_e_yn |
Data for example on empirical confidence interval for OHS. |
ci_mincost |
Confidence interval for minimum total cost, when estimated using parametric method |
ci_ohs |
Confidence interval for optimal holdout size, when estimated using parametric method |
cov_fn |
Covariance function for Gaussian process |
data_example_simulation |
Data for vignette showing general example |
data_nextpoint_em |
Data for 'next point' demonstration vignette on algorithm comparison using emulation algorithm |
data_nextpoint_par |
Data for 'next point' demonstration vignette on algorithm comparison using parametric algorithm |
error_ohs_emulation |
Measure of error for emulation-based OHS emulation |
exp_imp_fn |
Expected improvement |
gen_base_coefs |
Coefficients for imperfect risk score |
gen_preds |
Generate matrix of random observations |
gen_resp |
Generate response |
grad_mincost_powerlaw |
Gradient of minimum cost (power law) |
grad_nstar_powerlaw |
Gradient of optimal holdout size (power law) |
logistic |
Logistic |
logit |
Logit |
model_predict |
Make predictions |
model_train |
Train model (wrapper) |
mu_fn |
Updating function for mean. |
next_n |
Finds best value of n to sample next |
ohs_array |
Data for vignette on algorithm comparison |
ohs_resample |
Data for vignette on algorithm comparison |
optimal_holdout_size |
Estimate optimal holdout size under parametric assumptions |
optimal_holdout_size_emulation |
Estimate optimal holdout size under semi-parametric assumptions |
oracle_pred |
Generate responses |
params_aspre |
Parameters of reported ASPRE dataset |
plot.optholdoutsize |
Plot estimated cost function |
plot.optholdoutsize_emul |
Plot estimated cost function using emulation (semiparametric) |
powerlaw |
Power law function |
powersolve |
Fit power law curve |
powersolve_general |
General solver for power law curve |
powersolve_se |
Standard error matrix for learning curve parameters (power law) |
psi_fn |
Updating function for variance. |
sens10 |
Sensitivity at theshold quantile 10% |
sim_random_aspre |
Simulate random dataset similar to ASPRE training data |
split_data |
Split data |