Statistical Package for Reliability Data Analysis
Create an object for cumulative exposure
Mixed primal-dual bases algorithm for estimation of parameters with re...
Functions for estimating parameters in the linear/nonlinear mixed mode...
i_spline basis
Kaplan-Meier Location
Parametric Fitting for Lifetime Data
Calculate MLE for Lifetime Distribution
M_splines basis
Splines basis functions
The Standard Largest Extreme Value Distribution
Plot function for the class of "deglmx".
The Standard Smallest Extreme Value Distribution
Statistical Package for Reliability Data Analysis
Summaries of "Lifedata.MLE" Object
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.