seq_mr_nexp_mean: seq_mr_nexp_mean

In yelleKneK/SMSD: Sequential Methods for Study Design

seq_mr_nexp_mean

Description

Purely Sequential approach to Get Minimum Risk Point Estimation for negative exponential random variables

Usage

seq_mr_nexp_mean(
  data,
  A,
  c,
  k,
  t,
  pilot = FALSE,
  verbose = FALSE,
  na.rm = TRUE
)

Arguments

data	The data for which to calculate the minimum risk point.
A	The loss function constant.
c	The cost of unit sample.
k	Loss function index 1.
t	Loss function index 2.
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 calculated risk, the sample size, mean, standard deviation, and an indicator of if the criterion was satisfied.

Author(s)

Bhargab Chattopadhyay [e-mail], Neetu Shah [e-mail], Ken Kelley [e-mail]

References

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

Examples

pilot_ss <- seq_mr_nexp_mean(A=500, c=0.01, k=1, t=2, pilot=TRUE)
SLS <- rexp(pilot_ss, rate=1)
seq_mr_nexp_mean(data=SLS, A=500, c=0.01, k=1, t=2, pilot=FALSE)

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