Package: cond 1.2-3.1

cond: Approximate Conditional Inference for Logistic and Loglinear Models

Higher order likelihood-based inference for logistic and loglinear models.

Authors:S original by Alessandra R. Brazzale <[email protected]>. R port by Alessandra R. Brazzale <[email protected]>, following earlier work by Douglas Bates.

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cond/json (API)

# Install 'cond' in R:

install.packages('cond', repos = c('https://arbrazzale.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

aids - AIDS Symptoms and AZT Use Data
airway - Airway Data
babies - Crying Babies Data
dormicum - Dormicum Data
fraudulent - Fraudulent Automobile Insurance Claims Data
fungal - Fungal Infections Treatment Data
rabbits - Rabbits Data
urine - Urine Data

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.51 score 2 packages 27 scripts 248 downloads 2 mentions 8 exports 4 dependencies

Last updated 7 years agofrom:9e8c868321. Checks:OK: 1 NOTE: 6. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 09 2024
R-4.5-win	NOTE	Nov 09 2024
R-4.5-linux	NOTE	Nov 09 2024
R-4.4-win	NOTE	Nov 09 2024
R-4.4-mac	NOTE	Nov 09 2024
R-4.3-win	NOTE	Nov 09 2024
R-4.3-mac	NOTE	Nov 09 2024

Exports:cond cond.glm family.cond family.summary.cond plot.cond print.cond print.summary.cond summary.cond

Dependencies:lattice Matrix statmod survival

hoa: An R Package Bundle for Higher Order Likelihood Inference

Rendered fromRnews-paper.Rnwusingutils::Sweaveon Nov 09 2024.

Last update: 2014-06-27
Started: 2014-06-27

Citation

Readme and manuals

Help Manual

Help page	Topics
Approximate conditional inference for logistic and loglinear models	cond-package
AIDS Symptoms and AZT Use Data	aids
Airway Data	airway
Crying Babies Data	babies
Approximate Conditional Inference - Generic Function	cond
Approximate Conditional Inference for Logistic and Loglinear Models	cond.glm
Approximate Conditional Inference Object	cond.object
Dormicum Data	dormicum
Use family() on a ``cond'' object	family.cond
Use family() on a ``summary.cond'' object	family.summary.cond
Fraudulent Automobile Insurance Claims Data	fraudulent
Fungal Infections Treatment Data	fungal
Generate Plots for an Approximate Conditional Inference Object	plot.cond
Use print() on a ``summary.cond'' object	print.summary.cond
Rabbits Data	rabbits
Summary Method for Objects of Class ``cond''	summary.cond
Urine Data	urine