KDEmcmc
Kernel Density Estimation with a Markov Chain Monte Carlo Sample
Provides methods for selecting the optimal bandwidth in kernel density estimation for dependent samples, such as those generated by Markov chain Monte Carlo (MCMC). Implements a modified biased cross-validation (mBCV) approach that accounts for sample dependence, improving the accuracy of estimated density functions.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.0.2 |
rolling linux/jammy R-4.5 | KDEmcmc_0.0.2.tar.gz |
90.9 KiB |
0.0.2 |
rolling linux/noble R-4.5 | KDEmcmc_0.0.2.tar.gz |
93.6 KiB |
0.0.2 |
rolling source/ R- | KDEmcmc_0.0.2.tar.gz |
15.6 KiB |
0.0.2 |
latest linux/jammy R-4.5 | KDEmcmc_0.0.2.tar.gz |
90.9 KiB |
0.0.2 |
latest linux/noble R-4.5 | KDEmcmc_0.0.2.tar.gz |
93.6 KiB |
0.0.2 |
latest source/ R- | KDEmcmc_0.0.2.tar.gz |
15.6 KiB |
0.0.2 |
2026-04-26 source/ R- | KDEmcmc_0.0.2.tar.gz |
15.6 KiB |
0.0.2 |
2026-04-23 source/ R- | KDEmcmc_0.0.2.tar.gz |
15.6 KiB |
0.0.2 |
2026-04-09 windows/windows R-4.5 | KDEmcmc_0.0.2.zip |
413.5 KiB |