Package: hashprng 0.2.0.1000

Carl Pearson

hashprng: Hash-Based Matching Pseudo-Random Number Generation

Provides helper functions for use of hash-based matching (HBM) for pseudo-random number generation (PRNG) in stochastic simulations. HBM-PRNG is an approach to simplify matching synthetic experiment samples, which ensures that matched runs different only in the focal parameters, not in their chance events.

Authors:Carl Pearson [aut, cre]

hashprng_0.2.0.1000.tar.gz
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hashprng.pdf |hashprng.html
hashprng/json (API)
NEWS

# Install 'hashprng' in R:
install.packages('hashprng', repos = c('https://epinowcast.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/epinowcast/hashprng/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

stochastic-simulationcpp

3.30 score 2 stars 5 scripts 2 exports 1 dependencies

Last updated 1 years agofrom:3c8c2ea5bc (on v0.2.0). Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 08 2024
R-4.5-win-x86_64OKDec 08 2024
R-4.5-linux-x86_64OKDec 08 2024
R-4.4-win-x86_64OKDec 08 2024
R-4.4-mac-x86_64OKDec 08 2024
R-4.4-mac-aarch64OKDec 08 2024
R-4.3-win-x86_64OKDec 08 2024
R-4.3-mac-x86_64OKDec 08 2024
R-4.3-mac-aarch64OKDec 08 2024

Exports:hash_salthash_seed

Dependencies:Rcpp

Hash-based Matched Pseudo-Random Number Generation

Rendered fromhashprng.Rmdusingknitr::rmarkdownon Dec 08 2024.

Last update: 2023-08-04
Started: 2023-08-04