shock

A data frame with 38 observations and 3 variables.

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.

Yili Hong

SPREDA

Statistical Package for Reliability Data Analysis

Yimeng Xie

Zhibing Xu

shock function

<dl>
 <dt><code>Distance</code></dt>
<dd>a numeric vector</dd> <dt><code>Mode</code></dt>
<dd>a factor with levels <code>Censored</code> <code>Mode1</code> <code>Mode2</code></dd> <dt><code>Censor</code></dt>
<dd>a numeric vector</dd> 
</dl>

Format

Shock Absorber Failure Data — shock

<dl>
 <dt><code>Distance</code></dt>
<dd>a numeric vector</dd>

 <dt><code>Mode</code></dt>
<dd>a factor with levels <code>Censored</code> <code>Mode1</code> <code>Mode2</code></dd>

 <dt><code>Censor</code></dt>
<dd>a numeric vector</dd>

 
</dl>

shock: Shock Absorber Failure Data

Description

Usage

Arguments

Format