Privacy-Preserving Meta-Analysis via Low-Rank Basis Hunting

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Documentation for package ‘MetaHunt’ version 0.1.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

apply_wrapper	Reduce predicted functions to scalars via a user-supplied wrapper
build_grid	Build a shared evaluation grid from a reference dataset
coef.metahunt_weight_model	Extract coefficients from a MetaHunt weight model
conformal_from_fit	Split conformal intervals from a pre-fit MetaHunt pipeline
coverage	Empirical coverage of a conformal prediction-interval object
cross_conformal	Cross-conformal prediction intervals (pooled K-fold scores)
cv_error_curve	Cross-validated prediction-error curve for basis-rank selection
dfspa	Denoised functional Successive Projection Algorithm (d-fSPA)
fit_weight_model	Fit a weight model mapping study-level covariates to simplex weights
f_hat_from_models	Build the 'F_hat' matrix from a list of fitted study-level models
metahunt	Fit the full MetaHunt pipeline
minmax_regret	Minimax-regret aggregator for multisite function-valued estimands
plot.metahunt	Plot recovered basis functions from a MetaHunt fit
plot.metahunt_conformal	Plot a conformal prediction-interval object
predict.metahunt	Predict target functions (or scalar summaries) from a MetaHunt fit
predict.metahunt_weight_model	Predict simplex weights for new study-level covariates
predict_target	Predict the target function for new study-level covariates
print.metahunt_denoising_search	Print method for d-fSPA denoising parameter search results
print.summary.metahunt	Print a 'summary.metahunt' object
project_to_simplex	Project study-level functions onto the simplex spanned by basis functions
reconstruction_error_curve	Reconstruction-error curve for basis-rank selection
select_denoising_params	Choose d-fSPA denoising parameters by cross-validation
split_conformal	Split conformal prediction intervals for target-function predictions
summary.metahunt	Summarise a MetaHunt fit
summary.metahunt_conformal	Summarise a conformal prediction-interval object