findrelation

iVar

iResp

What model fit parameter is used for ranking? (Default: adj.R2)

criterion

A vector of model names chosen from "SL", "Quad", "SQuad", "Exp", "Log", "nls","CP"

modelNames

TRUE/FALSE Is this a 'strength' type model fitting? (whether to use ^2 and sqrt functions)

A dataframe of all results, passed in by the netSEMm function

cRes.all

A dataframe of best results, passed in by the netSEMm function

cRes.best

A dataframe of results to print, passed in by the netSEMm function

cRes.print

A dataframe of data values, passed in by the netSEMm function

A vector of nls initialization coefficients, passed in by the netSEMm function

nlsInits

number of cells in the print variable, value passed in by the netSEmm function

nRes

Find relationship between any two variables.

The network structural equation modeling conducts a network statistical analysis
on a data frame of coincident observations of multiple continuous variables [1].
It builds a pathway model by exploring a pool of domain knowledge guided candidate statistical
relationships between each of the variable pairs, selecting the 'best fit' on
the basis of a specific criteria such as adjusted r-squared value.
This work was funded under U. S. Dept. of Energy, Prime Award No. DE-E-0004946,
Award Agreement No. 60220829-51077-T.
[1] Bruckman, Laura S., Nicholas R. Wheeler, Junheng Ma, Ethan Wang, Carl K. Wang, Ivan Chou,
Jiayang Sun, and Roger H. French. (2013) <doi:10.1109/ACCESS.2013.2267611>.

Wei-Heng Huang

netSEM

Network Structural Equation Modeling

Nicholas Wheeler

Addison Klinke

Yifan Xu

Wenyu Du

Amit K. Verma

Abdulkerim Gok

Devin Gordon

Yu Wang

Jiqi Liu

Alan Curran

Justin Fada

Xuan Ma

Jennifer Braid

Jennifer Carter

Laura Bruckman

Roger French

findrelation function

<dl><dt>iVar</dt>
<dd>The first parameter.</dd>
<dt>iResp</dt>
<dd>The second parameter.</dd>
<dt>criterion</dt>
<dd>What model fit parameter is used for ranking? (Default: adj.R2)</dd>
<dt>modelNames</dt>
<dd>A vector of model names chosen from "SL", "Quad", "SQuad", "Exp", "Log", "nls","CP"</dd>
<dt>str</dt>
<dd>TRUE/FALSE Is this a 'strength' type model fitting? (whether to use ^2 and sqrt functions)</dd>
<dt>cRes.all</dt>
<dd>A dataframe of all results, passed in by the netSEMm function</dd>
<dt>cRes.best</dt>
<dd>A dataframe of best results, passed in by the netSEMm function</dd>
<dt>cRes.print</dt>
<dd>A dataframe of results to print, passed in by the netSEMm function</dd>
<dt>x</dt>
<dd>A dataframe of data values, passed in by the netSEMm function</dd>
<dt>nlsInits</dt>
<dd>A vector of nls initialization coefficients, passed in by the netSEMm function</dd>
<dt>nRes</dt>
<dd>number of cells in the print variable, value passed in by the netSEmm function</dd></dl>

Arguments

Find relationship between any two variables — findrelation

<dl>

<dt>iVar</dt>
<dd>The first parameter.</dd>


<dt>iResp</dt>
<dd>The second parameter.</dd>


<dt>criterion</dt>
<dd>What model fit parameter is used for ranking? (Default: adj.R2)</dd>


<dt>modelNames</dt>
<dd>A vector of model names chosen from "SL", "Quad", "SQuad", "Exp", "Log", "nls","CP"</dd>


<dt>str</dt>
<dd>TRUE/FALSE Is this a 'strength' type model fitting? (whether to use ^2 and sqrt functions)</dd>


<dt>cRes.all</dt>
<dd>A dataframe of all results, passed in by the netSEMm function</dd>


<dt>cRes.best</dt>
<dd>A dataframe of best results, passed in by the netSEMm function</dd>


<dt>cRes.print</dt>
<dd>A dataframe of results to print, passed in by the netSEMm function</dd>


<dt>x</dt>
<dd>A dataframe of data values, passed in by the netSEMm function</dd>


<dt>nlsInits</dt>
<dd>A vector of nls initialization coefficients, passed in by the netSEMm function</dd>


<dt>nRes</dt>
<dd>number of cells in the print variable, value passed in by the netSEmm function</dd>

</dl>

findrelation: Find relationship between any two variables

Description

Usage

Value

Arguments