apply_norm

<code>apply_norm</code> applies a normalization factor

Performs survival analysis using general non-linear models. Risk models can be the sum or product of terms. Each term is the product of exponential/linear functions of covariates. Additionally sub-terms can be defined as a sum of exponential, linear threshold, and step functions. Cox Proportional hazards, Poisson, and Fine-Gray competing risks regression are supported. This work was sponsored by NASA Grants 80NSSC19M0161 and 80NSSC23M0129 through a subcontract from the National Council on Radiation Protection and Measurements (NCRP). The computing for this project was performed on the Beocat Research Cluster at Kansas State University, which is funded in part by NSF grants CNS-1006860, EPS-1006860, EPS-0919443, ACI-1440548, CHE-1726332, and NIH P20GM113109.

Eric Giunta

Colossus

"Risk Model Regression and Analysis with Complex Non-Linear
Models"

Amir Bahadori

Dan Andresen

Linda Walsh

Benjamin French

Lawrence Dauer

John Boice Jr

Kansas State University 

NASA 

NCRP 

NRC 

apply_norm function

<dl><dt>df</dt>
<dd>The data.table with columns to be normalized</dd>
<dt>norm</dt>
<dd>The normalization option used, currently max or mean</dd>
<dt>names</dt>
<dd>columns for elements of the model, used to identify data columns</dd>
<dt>input</dt>
<dd>boolean if the normalization is being performed on the input values or on an output</dd>
<dt>values</dt>
<dd>list of values using during normalization</dd>
<dt>model_control</dt>
<dd>controls which alternative model options are used, see the Control_Options vignette for further details</dd></dl>

Arguments

Automatically applies a normalization to either an input or output — apply_norm

<dl>

<dt>df</dt>
<dd>The data.table with columns to be normalized</dd>


<dt>norm</dt>
<dd>The normalization option used, currently max or mean</dd>


<dt>names</dt>
<dd>columns for elements of the model, used to identify data columns</dd>


<dt>input</dt>
<dd>boolean if the normalization is being performed on the input values or on an output</dd>


<dt>values</dt>
<dd>list of values using during normalization</dd>


<dt>model_control</dt>
<dd>controls which alternative model options are used, see the Control_Options vignette for further details</dd>

</dl>

Automatically applies a normalization to either an input or output

apply_norm: Automatically applies a normalization to either an input or output

Description

Usage

Value

Arguments

See Also