logConCIfunctions

ftilde

c2hat

rLCD

Functions that are used by <code>logConCI</code> and are not intended to be called by the user.

htest

nonparametric

Given independent and identically distributed observations X(1), ..., X(n), compute the maximum likelihood estimator (MLE) of a density as well as a smoothed version of it under the assumption that the density is log-concave, see Rufibach (2007) and Duembgen and Rufibach (2009). The main function of the package is 'logConDens' that allows computation of the log-concave MLE and its smoothed version. In addition, we provide functions to compute (1) the value of the density and distribution function estimates (MLE and smoothed) at a given point (2) the characterizing functions of the estimator, (3) to sample from the estimated distribution, (5) to compute a two-sample permutation test based on log-concave densities, (6) the ROC curve based on log-concave estimates within cases and controls, including confidence intervals for given values of false positive fractions (7) computation of a confidence interval for the value of the true density at a fixed point. Finally, three datasets that have been used to illustrate log-concave density estimation are made available.

Kaspar Rufibach

logcondens

Estimate a Log-Concave Probability Density from Iid Observations

logConCIfunctions function

Mahdis Azadbakhsh
Hanna Jankowski, <a href="/link/hkj%40yorku.ca?package=logcondens&version=2.1.8" data-mini-rdoc="logcondens::hkj@yorku.ca">hkj@yorku.ca</a>

Author

Functions that are used by logConCI — logConCIfunctions

Mahdis Azadbakhsh
Hanna Jankowski, <a href='mailto:hkj@yorku.ca'>hkj@yorku.ca</a>

logConCIfunctions: Functions that are used by logConCI

Description

Arguments

Author

References