severity-package: Mayo's Post-data Severity Evaluation

In severity: Mayo's Post-data Severity Evaluation

Description

This package contains functions for calculating severity and generating severity curves. Specifically, the simple case of the one-parameter Normal distribution (i.e., with known variance) is considered.

Details

Package:	severity
Type:	Package
Version:	2.0
Date:	2013-03-27
License:	GPL (>= 2)

There is one function in this package, which is called severity: it (1) computes severity at various discrepancies (from the null hypothesis) for the hypothesis test H_{0}: μ = μ_{0} vs H_{1}: μ > μ_{0}, where μ_{0} is the hypothesized value; and (2) plots both the severity curve(s) and the power curve on a single plot.

*** The difference between this version and previous versions is that one more input is added for additional flexibility: the user is now able to control the hypothesized value of the (unknown) parameter μ. ***

Author(s)

Nicole Mee-Hyaang Jinn

Maintainer: Nicole Mee-Hyaang Jinn <[e-mail]>

References

Mayo, Deborah G. 2012. “Statistical Science Meets Philosophy of Science Part 2: Shallow Versus Deep Explorations.” Rationality, Markets and Morals: Studies at the Intersection of Philosophy and Economics 3 (Special Topic: Statistical Science and Philosophy of Science) (September 26): 71-107. http://www.rmm-journal.com/downloads/Article_Mayo2.pdf.

Mayo, Deborah G., and David R. Cox. 2010. “Frequentist Statistics as a Theory of Inductive Inference.” In Error and Inference: Recent Exchanges on Experimental Reasoning, Reliability, and the Objectivity and Rationality of Science, edited by Deborah G. Mayo and Aris Spanos, 247-274. Cambridge: Cambridge University Press.

Mayo, Deborah G., and Aris Spanos. 2006. “Severe Testing as a Basic Concept in a Neyman-Pearson Philosophy of Induction.” The British Journal for the Philosophy of Science 57 (2) (June 1): 323-357. doi:10.2307/3873470. http://www.jstor.org/stable/3873470.

Mayo, Deborah G., and Aris Spanos. 2011. “Error Statistics.” In Philosophy of Statistics, edited by Prasanta S. Bandyopadhyay and Malcom R. Forster, 7:153-198. Elsevier.

Examples

library(severity)
mu0 <- 5
sigma <- 2
n <- 100
alpha <- 0.025
xbar <- c(5.39, 5.30, 5.10, 5.40, 5.60, 5.85)
(sev <- severity(mu0 = mu0, xbar = xbar, sigma = sigma, n = n, alpha = alpha))

severity documentation built on May 2, 2019, 3:40 p.m.