Description: Contains functions to compute and plot confidence distributions, confidence densities, p-value functions and s-value (surprisal) functions for several commonly used estimates. Instead of just calculating one p-value and one confidence interval, p-value functions display p-values and confidence intervals for many levels thereby allowing to gauge the compatibility of several parameter values with the data. These methods are discussed by Infanger D, Schmidt-Trucksäss A. (2019) <doi:10.1002/sim.8293>; Poole C. (1987) <doi:10.2105/AJPH.77.2.195>; Schweder T, Hjort NL. (2002) <doi:10.1111/1467-9469.00285>; Bender R, Berg G, Zeeb H. (2005) <doi:10.1002/bimj.200410104> ; Singh K, Xie M, Strawderman WE. (2007) <doi:10.1214/074921707000000102>; Rothman KJ, Greenland S, Lash TL. (2008, ISBN:9781451190052); Amrhein V, Trafimow D, Greenland S. (2019) <doi:10.1080/00031305.2018.1543137>; Greenland S. (2019) <doi:10.1080/00031305.2018.1529625> and Rafi Z, Greenland S. (2020) <doi:10.1186/s12874-020-01105-9>.

Packaged: 2021-11-30 20:48:54 UTC; Denis Infanger

Description: The calculation of p-variation. Now it is in testing.

Title: p-variation, calculation and application
Description: The calculation of p-variation of the finite sample data

Title: the Calculation and Application of p-variation
Suggests: e1071, testthat, knitr, formatR

Title: Calculation and Application of p-variation

Title: Calculation and Application of p-Variation
Description: The calculation of p-variation of the finite sample data.
Suggests: e1071, testthat, knitr, formatR,

This package is a realisation of the procedure described in Butkus, V. & Norvaisa, R. Lith Math J (2018). <doi: 10.1007/s10986-018-9414-3>
The formal definitions and reference into literature are given in vignette.

Author: Niki Zumbrunnen <niki.zumbrunnen@stat.unibe.ch>, Lutz Duembgen
Description: Computes nonparametric p-values for the potential class
memberships of new observations as well as cross-validated
p-values for the training data. The p-values are based on
permutation tests applied to an estimated Bayesian likelihood
ratio, using a plug-in statistic for the Gaussian model, 'k
nearest neighbors' or 'weighted nearest neighbors'.
Additionally, it provides graphical displays and quantitative