myecdf

Calculate Empirical Cumulative Distribution Function

Provides tools for identifying subgroups within populations based on individual response patterns to specific interventions or treatments. Designed to support researchers and clinicians in exploring heterogeneous treatment effects and developing personalized therapeutic strategies. Offers functionality for analyzing and visualizing the interplay between two variables, thereby enhancing the interpretation of social sustainability metrics. The package focuses on bivariate discriminant analysis and aims to clarify relationships between indicator variables.

Franziska Dorn

BRPL

Methods for Bivariate Poverty Line Calculations

René-Marcel Kruse

Thomas Kneib

myecdf function

<dl><dt>data</dt>
<dd>A data frame containing the variable</dd>
<dt>var</dt>
<dd>Character string specifying the variable name</dd>
<dt>min.var</dt>
<dd>Minimum value for the variable</dd></dl>

Arguments

Calculate Empirical Cumulative Distribution Function — myecdf

<dl>

<dt>data</dt>
<dd>A data frame containing the variable</dd>


<dt>var</dt>
<dd>Character string specifying the variable name</dd>


<dt>min.var</dt>
<dd>Minimum value for the variable</dd>

</dl>

myecdf: Calculate Empirical Cumulative Distribution Function

Description

Usage

Value

Arguments