Package: SPREDA 1.1
SPREDA: Statistical Package for Reliability Data Analysis
The Statistical Package for REliability Data Analysis (SPREDA) implements recently-developed statistical methods for the analysis of reliability data. Modern technological developments, such as sensors and smart chips, allow us to dynamically track product/system usage as well as other environmental variables, such as temperature and humidity. We refer to these variables as dynamic covariates. The package contains functions for the analysis of time-to-event data with dynamic covariates and degradation data with dynamic covariates. The package also contains functions that can be used for analyzing time-to-event data with right censoring, and with left truncation and right censoring. Financial support from NSF and DuPont are acknowledged.
Authors:
SPREDA_1.1.tar.gz
SPREDA_1.1.zip(r-4.5)SPREDA_1.1.zip(r-4.4)SPREDA_1.1.zip(r-4.3)
SPREDA_1.1.tgz(r-4.4-any)SPREDA_1.1.tgz(r-4.3-any)
SPREDA_1.1.tar.gz(r-4.5-noble)SPREDA_1.1.tar.gz(r-4.4-noble)
SPREDA_1.1.tgz(r-4.4-emscripten)SPREDA_1.1.tgz(r-4.3-emscripten)
SPREDA.pdf |SPREDA.html✨
SPREDA/json (API)
| # Install 'SPREDA' in R: |
| install.packages('SPREDA', repos = c('https://yili-hong.r-universe.dev', 'https://cloud.r-project.org')) |
- Coatingenv - Dynamic covariates for the coating data.
- Coatingout - Dynamic covariates for coating data
- Prod2.fai.dat - Dataset of failure information of Product 2.
- Prod2.xt.dat - Dataset of covariate information of Produce 2.
- shock - Shock Absorber Failure Data
- testdata - Testdata
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 6 years agofrom:0493a23382. Checks:OK: 5 NOTE: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 27 2024 |
| R-4.5-win | NOTE | Oct 27 2024 |
| R-4.5-linux | NOTE | Oct 27 2024 |
| R-4.4-win | OK | Oct 27 2024 |
| R-4.4-mac | OK | Oct 27 2024 |
| R-4.3-win | OK | Oct 27 2024 |
| R-4.3-mac | OK | Oct 27 2024 |
Exports:ce.dat.prepclmeclscoef.deglmx.MLEcoef.Lifedata.MLEcoefinitial.ftndata.pre.fundeglmxdlevdsevgetCovgetnamesgetRanNamei.spline.xkaplan.meier.locationLifedata.MLElifetime.mlelogLik.Lifedata.MLEm.spline.xmatch.dat.funMIC.splines.basisminiusloglik.ce.xt.levminiusloglik.ce.xt.logisminiusloglik.ce.xt.normminiusloglik.ce.xt.sevminiusloglik.lev.wtsminiusloglik.logis.wtsminiusloglik.normal.wtsminiusloglik.sevminiusloglik.sev.wtsminus.log.lik.nlmeminus.loglik.lmemle.obj.to.fit.objoptim.ftn.2optim.step1.2optim.step2.2plevplot.MICsplinesplotdeglmxprint.deglmxprint.Lifedata.MLEprint.summary.Lifedata.MLEpsevPxqlevqsevrlevrsevsqrt_matsummary.Lifedata.MLExmat.obj.to.xmatxmat.to.cumsum
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Statistical Package for Reliability Data Analysis | SPREDA-package SPREDA |
| Create an object for cumulative exposure | ce.dat.prep |
| Mixed primal-dual bases algorithm for estimation of parameters with restriction. | cls |
| Dynamic covariates for the coating data. | Coatingenv |
| Dynamic covariates for coating data | Coatingout |
| Functions for estimating parameters in the linear/nonlinear mixed models with dynamic covariates. | clme coef.deglmx.MLE coefinitial.ftn data.pre.fun deglmx getCov getnames getRanName match.dat.fun minus.log.lik.nlme minus.loglik.lme mle.obj.to.fit.obj optim.ftn.2 optim.step1.2 optim.step2.2 plot.MICsplines print.deglmx Px sqrt_mat xmat.obj.to.xmat xmat.to.cumsum |
| i_spline basis | i.spline.x |
| Kaplan-Meier Location | kaplan.meier.location |
| Parametric Fitting for Lifetime Data | coef.Lifedata.MLE Lifedata.MLE logLik.Lifedata.MLE miniusloglik.ce.xt.lev miniusloglik.ce.xt.logis miniusloglik.ce.xt.norm miniusloglik.ce.xt.sev miniusloglik.lev.wts miniusloglik.logis.wts miniusloglik.normal.wts miniusloglik.sev.wts print.Lifedata.MLE |
| Calculate MLE for Lifetime Distribution | lifetime.mle miniusloglik.sev |
| M_splines basis | m.spline.x |
| Splines basis functions | MIC.splines.basis |
| The Standard Largest Extreme Value Distribution | dlev plev qlev rlev |
| Plot function for the class of "deglmx". | plotdeglmx |
| Dataset of failure information of Product 2. | Prod2.fai.dat |
| Dataset of covariate information of Produce 2. | Prod2.xt.dat |
| The Standard Smallest Extreme Value Distribution | dsev psev qsev rsev |
| Shock Absorber Failure Data | shock |
| Summaries of "Lifedata.MLE" Object | print.summary.Lifedata.MLE summary.Lifedata.MLE |
| Testdata | testdata |
