Package: esreg 0.6.2

esreg: Joint Quantile and Expected Shortfall Regression

Simultaneous modeling of the quantile and the expected shortfall of a response variable given a set of covariates, see Dimitriadis and Bayer (2019) <doi:10.1214/19-EJS1560>.

Authors:Sebastian Bayer [aut, cre], Timo Dimitriadis [aut]

esreg_0.6.2.tar.gz
esreg_0.6.2.zip(r-4.7)esreg_0.6.2.zip(r-4.6)esreg_0.6.2.zip(r-4.5)
esreg_0.6.2.tgz(r-4.6-x86_64)esreg_0.6.2.tgz(r-4.6-arm64)esreg_0.6.2.tgz(r-4.5-x86_64)esreg_0.6.2.tgz(r-4.5-arm64)
esreg_0.6.2.tar.gz(r-4.7-arm64)esreg_0.6.2.tar.gz(r-4.7-x86_64)esreg_0.6.2.tar.gz(r-4.6-arm64)esreg_0.6.2.tar.gz(r-4.6-x86_64)
esreg_0.6.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
esreg/json (API)
NEWS

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

Bug tracker:https://github.com/bayerse/esreg/issues

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

On CRAN:

Conda:

expected-shortfallquantile-regressionvalue-at-riskopenblascpp

3.73 score 2 stars 1 packages 18 scripts 219 downloads 20 exports 10 dependencies

Last updated from:086e4fdfac. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK121
linux-devel-x86_64OK123
source / vignettesOK150
linux-release-arm64OK137
linux-release-x86_64OK120
macos-release-arm64OK95
macos-release-x86_64OK162
macos-oldrel-arm64OK127
macos-oldrel-x86_64OK256
windows-develOK146
windows-releaseOK106
windows-oldrelOK155
wasm-releaseOK96

Exports:cdf_at_quantileconditional_mean_sigmaconditional_truncated_variancedensity_quantile_functionesr_lossesr_rho_lpesregestfun.esregG_vecG1_funG1_prime_funG1_prime_prime_funG2_curly_funG2_funG2_prime_funG2_prime_primelambda_matrixsigma_matrixvcovAvcovB

Dependencies:FormulalatticeMASSMatrixMatrixModelsquantregRcppRcppArmadilloSparseMsurvival