Result for 29EF96858194F7A0596F860A474748C99D3349F7

Query result

Key Value
FileName./usr/lib64/R/library/quantreg/help/paths.rds
FileSize704
MD5D1C7EF2C1BF493E8B42578B7AD6B9E8C
SHA-129EF96858194F7A0596F860A474748C99D3349F7
SHA-256C7CBD1522E2A51F4FAF12165132BC35A4044BA8A8DBBADE9755A8B70B1B1EA0F
SSDEEP12:XOh+S7MuuwzqJhy7FQMUkJ8qW2lmh6+hlW3blsZCrSyoR9VMn:XOh+sOy7mMUkyX3k+nEsodCvMn
TLSHT13C019490AAE18D3DD67DCAB4CB07008D012E4FA3C8AF2E2223F2B48684524B259800B7
hashlookup:parent-total4
hashlookup:trust70

Network graph view

Parents (Total: 4)

The searched file hash is included in 4 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD5981E3FE0B1ACE969C1DDF0996A8A43A0
PackageArchx86_64
PackageDescriptionEstimation and inference methods for models of conditional quantiles: Linear and nonlinear parametric and non-parametric (total variation penalized) models for conditional quantiles of a univariate response and several methods for handling censored survival data. Portfolio selection methods based on expected shortfall risk are also now included. See Koenker (2006) <doi:10.1017/CBO9780511754098> and Koenker et al. (2017) <doi:10.1201/9781315120256>.
PackageNameR-quantreg
PackageReleaselp153.2.2
PackageVersion5.86
SHA-1BF1362FCE9828F553906B7798D91B2EBE490327C
SHA-2561F2354574F1B52607930E96AB17BF8EBEF8D9422FB91195F37190AC211DA73F0
Key Value
MD57DFB935CCAC9A22AF35A1A8814254055
PackageArchx86_64
PackageDescriptionEstimation and inference methods for models of conditional quantiles: Linear and nonlinear parametric and non-parametric (total variation penalized) models for conditional quantiles of a univariate response and several methods for handling censored survival data. Portfolio selection methods based on expected shortfall risk are also now included. See Koenker (2006) <doi:10.1017/CBO9780511754098> and Koenker et al. (2017) <doi:10.1201/9781315120256>.
PackageNameR-quantreg
PackageRelease2.6
PackageVersion5.86
SHA-109761D3FAFBC2E1B37CF30B9D6DA223D7DA1597F
SHA-2563D4E0D692C63C54E9C190ED377807B5A1806FA6568E2767458CC6D60133B2690
Key Value
MD50831899D0BAFB620A8AD82DED2F7436E
PackageArchx86_64
PackageDescriptionEstimation and inference methods for models of conditional quantiles: Linear and nonlinear parametric and non-parametric (total variation penalized) models for conditional quantiles of a univariate response and several methods for handling censored survival data. Portfolio selection methods based on expected shortfall risk are also now included. See Koenker (2006) <doi:10.1017/CBO9780511754098> and Koenker et al. (2017) <doi:10.1201/9781315120256>.
PackageNameR-quantreg
PackageReleaselp154.2.1
PackageVersion5.86
SHA-1775B0CAA73653E1CF4F2590032653B6BF8DEF5C7
SHA-2567B2A56C490E5ABB7443949713B7942C6C733CC4A44B572C1AF04E904F0BB0A9F
Key Value
MD55A7988BF946EEBF09E6DD56A0438902E
PackageArchx86_64
PackageDescriptionEstimation and inference methods for models of conditional quantiles: Linear and nonlinear parametric and non-parametric (total variation penalized) models for conditional quantiles of a univariate response and several methods for handling censored survival data. Portfolio selection methods based on expected shortfall risk are also now included. See Koenker (2006) <doi:10.1017/CBO9780511754098> and Koenker et al. (2017) <doi:10.1201/9781315120256>.
PackageNameR-quantreg
PackageReleaselp152.2.2
PackageVersion5.86
SHA-14DDCD2F4FEE5B0A63A7AB906D024C4F6AEFB618C
SHA-25610277A25A7B1C3DD740EFBB131A43A0255D34790E025F909A5D27538D890B4C8