HTDV
Hypothesis Testing for Dependent Variables with Unbalanced Data
Implements hierarchical Bayesian inference, robust frequentist inference, and distribution-free inference for dependent and unbalanced data under strong-mixing conditions. Supports triangular-array, weighted-sum and mixingale convergence regimes with Whittle and composite likelihoods, heteroskedasticity-and-autocorrelation-consistent variance estimation, block bootstrap with automatic block length, fixed-bandwidth HAR inference, adaptive conformal prediction, Bayesian decision under Region of Practical Equivalence, bridge-sampling Bayes factors, and predictive comparison via the Widely Applicable Information Criterion and leave-future-out cross-validation. Methods follow Andrews (1991) <doi:10.2307/2938229>, Kiefer and Vogelsang (2005) <doi:10.1017/S0266466605050565>, Patton, Politis and White (2009) <doi:10.1080/07474930802459016>, Vehtari, Gelman and Gabry (2017) <doi:10.1007/s11222-016-9696-4>, Kruschke (2018) <doi:10.1177/2515245918771304>, and Gibbs and Candes (2021) <doi:10.48550/arXiv.2106.00170>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.2.0 |
rolling linux/jammy R-4.5 | HTDV_0.2.0.tar.gz |
245.2 KiB |
0.2.0 |
rolling linux/noble R-4.5 | HTDV_0.2.0.tar.gz |
245.4 KiB |
0.2.0 |
rolling source/ R- | HTDV_0.2.0.tar.gz |
123.9 KiB |
0.2.0 |
latest linux/jammy R-4.5 | HTDV_0.2.0.tar.gz |
245.2 KiB |
0.2.0 |
latest linux/noble R-4.5 | HTDV_0.2.0.tar.gz |
245.4 KiB |
0.2.0 |
latest source/ R- | HTDV_0.2.0.tar.gz |
123.9 KiB |
0.2.0 |
2026-04-23 source/ R- | HTDV_0.2.0.tar.gz |
0 B |