Exponential

This creates a Curve object for a Exponential distribution. 
Curve objects contain all necessary information to describe a distribution, including functions and parameters describing it. 
Parameterisation follows that used by pexp etc. Note that lambda = 1/alpha from the Weibull constructor. See Details for more information on parameterisation.

Provides tools to assist planning and monitoring of time-to-event trials under complicated censoring assumptions and/or non-proportional hazards. There are three main components: The first is analytic calculation of predicted time-to-event trial properties, providing estimates of expected hazard ratio, event numbers and power under different analysis methods. The second is simulation, allowing stochastic estimation of these same properties. Thirdly, it provides parametric event prediction using blinded trial data, including creation of prediction intervals. Methods are based upon numerical integration and a flexible object-orientated structure for defining event, censoring and recruitment distributions (Curves).

James Bell

gestate

Generalised Survival Trial Assessment Tool Environment

Jasmin Ruehl

Exponential function

<dl><dt>lambda</dt>
<dd>Rate parameter for Exponential distribution.</dd></dl>

Arguments

Author

This creates a Curve object for a Exponential distribution. 
Curve objects contain all necessary information to describe a distribution, including functions and parameters describing it. 
Parameterisation follows that used by pexp etc. Note that lambda = 1/alpha from the Weibull constructor. See Details for more information on parameterisation.

Exponential Curve constructor function — Exponential

<dl>

<dt>lambda</dt>
<dd>Rate parameter for Exponential distribution.</dd>

</dl>

Exponential: Exponential Curve constructor function

Description

Usage

Arguments

Author

Details

Examples