ts_br_exp_mean: ts_br_exp_mean
In yelleKneK/SMSD: Sequential Methods for Study Design

ts_br_exp_mean

R Documentation

ts_br_exp_mean

Description

Two Stage approach to Get Bounded Risk Point Estimation for the mean of exponential random variables

Usage

ts_br_exp_mean(data, A, w, pilot = FALSE, verbose = FALSE, na.rm = TRUE)

Arguments

`data`	The data for which to calculate the bounded risk point.
`A`	The loss function constant.
`w`	The risk bound. A non-negative integer greater than zero.
`pilot`	Should a pilot sample be generated. True/False value. default value is `FALSE`.
`verbose`	Should the criterion be printed. Default is `FALSE`.
`na.rm`	This parameter controls whether NA values are removed from the data prior to calculation. Default is `TRUE`.

Value

The current sample size, the mean and an indicator of if the criterion is satisfied.

Author(s)

Bhargab Chattopadhyay Bhargab@iiitvadodara.ac.in, Neetu Shah 201451015@iiitvadodara.ac.in, Ken Kelley kkelley@nd.edu

References

Mukhopadhyay, N., \& de Silva, Basil M. (2009). Sequential Methods and Their Applications. New York: CRC Press.

Examples

pilot_ss <- ts_br_exp_mean(w=4, pilot=TRUE)
SLS <- rexp(pilot_ss, rate=2)
## Not run: 
SLS <- rexp(pilot_ss, rate=2)

## End(Not run)
SLS <- rexp(100, rate=2)
ts_br_exp_mean(SLS, A=100, w=4, pilot=FALSE)

yelleKneK/SMSD documentation built on Nov. 23, 2022, 6:40 p.m.