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marp

Model-averaged renewal process

https://github.com/kanji709/marp

Science Score: 13.0%

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    CITATION.cff file
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    Scientific vocabulary similarity
    Low similarity (9.8%) to scientific vocabulary
Last synced: 9 months ago · JSON representation

Repository

Model-averaged renewal process

Basic Info
  • Host: GitHub
  • Owner: kanji709
  • License: other
  • Language: R
  • Default Branch: master
  • Homepage:
  • Size: 757 KB
Statistics
  • Stars: 1
  • Watchers: 2
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 5 years ago · Last pushed over 1 year ago
Metadata Files
Readme Changelog License

README.md

marp

R CMD check <!-- badges: end -->

An R package to apply model-averaging on renewal process.

alt text

Install

You can install the released version of marp from GitHub with:

``` r if(!require(devtools)){ install.packages("devtools") library(devtools) }

devtools::install_github("kanji709/marp") ```

Example

Here is a basic example which shows you how to use marp:

``` r

load R package - marp

library(marp)

generate a small dataset

data <- rgamma(100,3,0.01)

set parameters

m <- 10 # number of iterations for MLE optimization t <- seq(100,200,by=10) # time intervals B <- 99 # number of bootstraps BB <- 99 # number of double-bootstrapps alpha <- 0.05 # confidence level y <- 304 # cut-off time point for probablity estimation model_gen <- 2 # specifying the data generating model (if known)

step one: fitting differnt renewal models

res1 <- marp::poissonrp(dat,t,y) res2 <- marp::gammarp(dat,t,m,y) res3 <- marp::loglogisrp(dat,t,m,y) res4 <- marp::weibullrp(dat,t,m,y) res5 <- marp::lognormrp(dat,t,y) res6 <- marp::bptrp(dat,t,m,y)

step two: model selection and obtain model-averaged estimates

res <- marp::marp(dat,t,m,y,which.model = 2)

step three: construct different confidence intervals (including model-averaged CIs)

ci <- marp::marpconfint(dat,m,t,B,BB,alpha,y,modelgen) ```

Owner

  • Name: Jie Kang
  • Login: kanji709
  • Kind: user

GitHub Events

Total
  • Member event: 2
  • Push event: 27
Last Year
  • Member event: 2
  • Push event: 27

Issues and Pull Requests

Last synced: over 1 year ago

All Time
  • Total issues: 0
  • Total pull requests: 9
  • Average time to close issues: N/A
  • Average time to close pull requests: about 4 hours
  • Total issue authors: 0
  • Total pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 9
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
Pull Request Authors
  • chrisdjscott (9)
Top Labels
Issue Labels
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Packages

  • Total packages: 1
  • Total downloads:
    • cran 191 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 1
  • Total maintainers: 1
cran.r-project.org: marp

Model-Averaged Renewal Process

  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 191 Last month
Rankings
Forks count: 28.8%
Dependent packages count: 29.8%
Stargazers count: 35.2%
Dependent repos count: 35.5%
Average: 41.6%
Downloads: 78.9%
Maintainers (1)
jkang@maths.otago.ac.nz
Last synced: over 1 year ago

Dependencies

DESCRIPTION cran
  • R >= 2.15 depends
  • VGAM * imports
  • gtools * imports
  • statmod * imports
  • stats * imports
  • devtools * suggests
  • knitr * suggests
  • roxygen2 * suggests
  • testthat >= 3.0.0 suggests
.github/workflows/check-standard.yml actions
  • actions/checkout v2 composite
  • actions/upload-artifact main composite
  • r-lib/actions/check-r-package v1 composite
  • r-lib/actions/setup-pandoc v1 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v1 composite