SPREDA-package: Statistical Package for Reliability Data Analysis

Description Details Author(s) References

Description

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.

Details

Package: SPREDA
Type: Package
Version: 1.0
Date: 2014-09-20
License: GPL-2

Contains functions that are useful for the analysis of reliability data.

Author(s)

Yili Hong, Yimeng Xie, and Zhibing Xu

Maintainer: Yili Hong <[email protected]>

References

Hong, Y., W. Q. Meeker, and J. D. McCalley (2009). Prediction of Remaining Life of Power Transformers Based on Left Truncated and Right Censored Lifetime Data. The Annals of Applied Statistics, Vol. 3, pp. 857-879.

Hong, Y. and Meeker, W. Q. (2010), Field-Failure and Warranty Prediction Using Auxiliary Use-rate Data. Technometrics, Vol. 52, pp. 148-159.

Hong, Y. and Meeker, W. Q. (2013), Field-Failure Predictions Based on Failure-time Data with Dynamic Covariate Information, Technometrics, Vol. 55, pp. 135-149.

Hong, Y. (2013), On Computing the Distribution Function for the Poisson Binomial Distribution, Computational Statistics and Data Analysis, Vol. 59, pp. 41-51.

Hong. Y., Y. Duan, W. Q. Meeker, D. L. Stanley, and X. Gu (2014), Statistical Methods for Degradation Data with Dynamic Covariates Information and an Application to Outdoor Weathering Data, Technometrics, DOI: 10.1080/00401706.2014.915891.

Meeker, W. Q. and L. A. Escobar (1998). Statistical Methods for Reliability Data. John Wiley & Sons.

Meeker, W. Q. and L. A. Escobar (2014). RSplida. http://www.public.iastate.edu/~stat533/.

Xu, Z., Y. Hong, and R. Jin (2014), Nonlinear General Path Models for Degradation Data with Dynamic Covariates, submitted.


SPREDA documentation built on May 29, 2017, 11:24 a.m.