[ ソース: r-cran-epir ]
パッケージ: r-cran-epir (2.0.19-1)
r-cran-epir に関するリンク
Debian の資源:
r-cran-epir ソースパッケージをダウンロード:
メンテナ:
外部の資源:
- ホームページ [cran.r-project.org]
類似のパッケージ:
GNU R Functions for analysing epidemiological data
A package for analysing epidemiological data. Contains functions for directly and indirectly adjusting measures of disease frequency, quantifying measures of association on the basis of single or multiple strata of count data presented in a contingency table, and computing confidence intervals around incidence risk and incidence rate estimates. Miscellaneous functions for use in meta-analysis, diagnostic test interpretation, and sample size calculations.
その他の r-cran-epir 関連パッケージ
|
|
|
|
-
- dep: r-api-4.0
- 以下のパッケージによって提供される仮想パッケージです: r-base-core
-
- dep: r-base-core (>= 4.0.3-1)
- GNU R core of statistical computation and graphics system
-
- dep: r-cran-biasedurn
- GNU R Biased Urn model distributions
-
- dep: r-cran-lubridate
- simplifies dealing with dates in R
-
- dep: r-cran-pander
- GNU R 'Pandoc' writer
-
- dep: r-cran-survival
- 生存率解析用 GNU R パッケージ
-
- sug: r-cran-foreign
- 他の統計システムのデータを読み書きするための GNU R パッケージ
-
- sug: r-cran-ggplot2
- implementation of the Grammar of Graphics
-
- sug: r-cran-knitr
- GNU R package for dynamic report generation using Literate Programming
-
- sug: r-cran-mapproj
- GNU R support for cartographic projections of map data
-
- sug: r-cran-maptools
- GNU R Tools for reading and handling spatial objects
-
- sug: r-cran-mass (>= 3.1-20)
- GNU R package of Venables and Ripley's MASS
-
- sug: r-cran-plyr
- tools for splitting, applying and combining data
-
- sug: r-cran-rcolorbrewer
- GNU R package providing suitable color palettes
-
- sug: r-cran-rgdal
- GNU R bindings for the geospatial data abstraction library
-
- sug: r-cran-rmarkdown
- convert R markdown documents into a variety of formats
-
- sug: r-cran-scales
- Scale functions for visualization
-
- sug: r-cran-spatstat
- GNU R Spatial Point Pattern analysis, model-fitting, simulation, tests
-
- sug: r-cran-spdata
- GNU R datasets for spatial analysis