fun_sphere_norm

Normalizes each row of a numeric dataframe or matrix to have unit L2 norm (Euclidean length). Each row is divided by its own length, projecting all rows onto the unit hypersphere. Useful for analyses where direction is important but magnitude should be removed.

ENA (Shaffer, D. W. (2017) Quantitative Ethnography. ISBN: 0578191687) is a method used to identify meaningful and quantifiable patterns in discourse or reasoning. ENA moves beyond the traditional frequency-based assessments by examining the structure of the co-occurrence, or connections in coded data. Moreover, compared to other methodological approaches, ENA has the novelty of (1) modeling whole networks of connections and (2) affording both quantitative and qualitative comparisons between different network models.   Shaffer, D.W., Collier, W., & Ruis, A.R. (2016).

Cody L Marquart

rENA

Epistemic Network Analysis

Zachari Swiecki

Wesley Collier

Brendan Eagan

Roman Woodward

David Williamson Shaffer

fun_sphere_norm function

<dl><dt>dfM</dt>
<dd>A data.frame or matrix. Each row is treated as a vector to compute its L2 norm.</dd></dl>

Arguments

Row-wise L2 (Sphere) Normalization — fun_sphere_norm

<dl>

<dt>dfM</dt>
<dd>A data.frame or matrix. Each row is treated as a vector to compute its L2 norm.</dd>

</dl>

fun_sphere_norm: Row-wise L2 (Sphere) Normalization

Description

Usage

Value

Arguments

Details

Examples