Package: LMN 1.1.2

LMN: Inference for Linear Models with Nuisance Parameters

Efficient Frequentist profiling and Bayesian marginalization of parameters for which the conditional likelihood is that of a multivariate linear regression model. Arbitrary inter-observation error correlations are supported, with optimized calculations provided for independent-heteroskedastic and stationary dependence structures.

Authors:Martin Lysy [aut, cre], Bryan Yates [aut]

LMN_1.1.2.tar.gz
LMN_1.1.2.zip(r-4.5)LMN_1.1.2.zip(r-4.4)LMN_1.1.2.zip(r-4.3)
LMN_1.1.2.tgz(r-4.5-x86_64)LMN_1.1.2.tgz(r-4.5-arm64)LMN_1.1.2.tgz(r-4.4-x86_64)LMN_1.1.2.tgz(r-4.4-arm64)LMN_1.1.2.tgz(r-4.3-x86_64)LMN_1.1.2.tgz(r-4.3-arm64)
LMN_1.1.2.tar.gz(r-4.5-noble)LMN_1.1.2.tar.gz(r-4.4-noble)
LMN_1.1.2.tgz(r-4.4-emscripten)LMN_1.1.2.tgz(r-4.3-emscripten)
LMN.pdf |LMN.html✨
LMN/json (API)
NEWS

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

Bug tracker:https://github.com/mlysy/lmn/issues

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

On CRAN:

Conda:

cpp

3.70 score 1 stars 8 scripts 262 downloads 7 exports 5 dependencies

Last updated 3 years agofrom:3ad355244e. Checks:11 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 18 2025
R-4.5-win-x86_64OKFeb 18 2025
R-4.5-mac-x86_64OKFeb 18 2025
R-4.5-mac-aarch64OKFeb 18 2025
R-4.5-linux-x86_64OKFeb 18 2025
R-4.4-win-x86_64OKFeb 18 2025
R-4.4-mac-x86_64OKFeb 18 2025
R-4.4-mac-aarch64OKFeb 18 2025
R-4.3-win-x86_64OKFeb 18 2025
R-4.3-mac-x86_64OKFeb 18 2025
R-4.3-mac-aarch64OKFeb 18 2025

Exports:list2mniwlmn_logliklmn_marglmn_postlmn_priorlmn_proflmn_suff

Dependencies:fftwR6RcppRcppEigenSuperGauss

LMN: Inference for Linear Models with Nuisance Parameters

Martin Lysy, Bryan Yates

Rendered fromLMN.Rmdusingknitr::rmarkdownon Feb 18 2025.

Last update: 2022-02-14
Started: 2019-04-09