concurve-package

A description of the concurve R package

Statistical Computations

Compute consonance and surprisal distribitions for a wide range of scenarios, along with likelihood functions.

curve_boot()

Generate Consonance Functions via Bootstrapping

curve_corr()

Consonance Functions for Correlations

curve_gen()

Consonance Functions For Linear Models, Generalized Linear Models, and Robust Linear Models

curve_lik()

Compute Profile Likelihood Functions

curve_lmer()

Consonance Functions For Linear & Non-Linear Mixed-Effects Models.

curve_mean()

Consonance Functions For Mean Differences

curve_meta()

Consonance Functions For Meta-Analytic Data

curve_rev()

Reverse Engineer Consonance / Likelihood Functions Using the Point Estimate and Confidence Limits

curve_surv()

Consonance Functions For Survival Data

Statistical Graphics

Plot the overall functions that were computed such as the consonance, surprisal, and likelihood functions.

ggcurve()

Plots Consonance, Surprisal, and Likelihood Functions

curve_compare()

Compare Two Functions and Produces An AUC Score

plot_compare()

Graph and Compare Consonance, Surprisal, and Likelihood Functions

Statistical Reporting

Display the tables showing relevant statistics from the initial computations.

curve_table()

Produce Tables For concurve Functions

Miscellaneous Functions

Some internal helper functions.

RobustMin()

Robust Min, an alternative to max() that doesn't throw a warning

RobustMax()

Robust Max, an alternative to max() that doesn't throw a warning