the r package threg to implement threshold regression models
Clicks: 146
ID: 198358
2015
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
30.0
/100
146 views
33 readers
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #69 of 98 articles by views in open geospatial data, software and standards
Most read
Least read
Bar heights use a square-root scale.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
This paper introduces the R package threg, which implements the estimation procedure of a threshold regression model, which is based on the first-hitting-time of a boundary by the sample path of a Wiener diffusion process. The threshold regression methodology is well suited to applications involving survival and time-to-event data, and serves as an important alternative to the Cox proportional hazards model.
This new package includes four functions: threg, and the methods hr, predict and plot for threg objects returned by threg. The threg function is the model-fitting function which is used to calculate regression coefficient estimates, asymptotic standard errors and p values. The hr method for threg objects is the hazard-ratio calculation function which provides the estimates of hazard ratios at selected time points for specified scenarios (based on given categories or value settings of covariates). The predict method for threg objects is used for prediction. And the plot method for threg objects provides plots for curves of estimated hazard functions, survival functions and probability density functions of the first-hitting-time; function curves corresponding to different scenarios can be overlaid in the same plot for comparison to give additional research insights.
| Reference Key |
xiao2015journalthe
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;Tao Xiao;G. A. Whitmore;Xin He;Mei-Ling Ting Lee |
| Journal | open geospatial data, software and standards |
| Year | 2015 |
| DOI |
10.18637/jss.v066.i08
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.