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logcondens (version 2.1.0)

Estimate a Log-Concave Probability Density from iid Observations

Description

Given independent and identically distributed observations X(1), ..., X(n), this package allows to 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.

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Version

Install

install.packages('logcondens')

Monthly Downloads

6,614

Version

2.1.0

License

GPL (>= 2)

Maintainer

Kaspar Rufibach

Last Published

December 16th, 2013

Functions in logcondens (2.1.0)

Jfunctions

Numerical Routine J and Some Derivatives
intECDF

Computes the Integrated Empirical Distribution Function at Arbitrary Real Numbers in s
intF

Computes the Integral of the estimated CDF at Arbitrary Real Numbers in s
Q00

Numerical Routine Q
reparametrizations

Changes Between Parametrizations
qloglin

Quantile Function In a Simple Log-Linear model
icmaLogCon

Computes a Log-Concave Probability Density Estimate via an Iterative Convex Minorant Algorithm
rlogcon

Generate random sample from the log-concave and the smoothed log-concave density estimator
logConROC

Compute ROC curve based on log-concave estimates for the constituent distributions
Local_LL

Value of the Log-Likelihood Function L, where Input is in Phi-Parametrization
logConDens

Compute log-concave density estimator and related quantities
reliability

Reliability dataset used to illustrate log-concave density estimation
Lhat_eta

Value of the Log-Likelihood Function L, where Input is in Eta-Parametrization
confIntBootLogConROC_t0

Function to compute a bootstrap confidence interval for the ROC curve at a given t, based on the log-concave ROC curve
Local_LL_all

Log-likelihood, New Candidate and Directional Derivative for L
logconTwoSample

Compute p-values for two-sample test based on log-concave CDF estimates
logcon-package

Estimate a Log-Concave Probability Density from iid Observations
logConCIfunctions

Functions that are used by logConCI
MLE

Unconstrained piecewise linear MLE
robust

Robustification and Hermite Interpolation for ICMA
quadDeriv

Gradient and Diagonal of Hesse Matrix of Quadratic Approximation to Log-Likelihood Function L
preProcess

Compute a weighted sample from initial observations
activeSetRoutines

Auxiliary Numerical Routines for the Function activeSetLogCon
isoMean

Pool-Adjacent Violaters Algorithm: Least Square Fit under Monotonicity Constraint
brightstar

Bright star dataset used to illustrate log-concave density estimation
ROCx

Compute ROC curve at a given x based on log-concave estimates for the constituent distributions
evaluateLogConDens

Evaluates the Log-Density MLE and Smoothed Estimator at Arbitrary Real Numbers xs
plot.dlc

Standard plots for a dlc object
summary.dlc

Summarizing log-concave density estimation
pancreas

Data from pancreatic cancer serum biomarker study
maxDiffCDF

Compute maximal difference between CDFs corresponding to log-concave estimates
quantilesLogConDens

Function to compute Quantiles of Fhat
activeSetLogCon

Computes a Log-Concave Probability Density Estimate via an Active Set Algorithm
logConCI

Compute pointwise confidence interval for a density assuming log-concavity