Compute the variance inflation factors (VIFs) for covariates in one level of the 
model (i.e., occupancy or detection). Calculation of VIFs follows the approach 
of function <code>vif</code> in package <code>car</code>, using the correlation matrix of 
fitted model parameters.

Fits hierarchical models of animal abundance and occurrence to data collected using survey methods such as point counts, site occupancy sampling, distance sampling, removal sampling, and double observer sampling. Parameters governing the state and observation processes can be modeled as functions of covariates. References: Kellner et al. (2023) <doi:10.1111/2041-210X.14123>, Fiske and Chandler (2011) <doi:10.18637/jss.v043.i10>.

Ken Kellner

unmarked

Models for Data from Unmarked Animals

Richard Chandler

Ian Fiske

David Miller

Andy Royle

Jeff Hostetler

Rebecca Hutchinson

Adam Smith

Lea Pautrel

Marc Kery

Mike Meredith

Auriel Fournier

Ariel Muldoon

Chris Baker

vif function

<dl> <dt>mod</dt>
<dd>An unmarked fit object.</dd> <dt>type</dt>
<dd>Level of the model for which to calculate VIFs (for example,
 <code>'state'</code>)</dd></dl>

Arguments

Compute Variance Inflation Factors for an unmarkedFit Object. — vif

<dl>

 <dt>mod</dt>
<dd>An unmarked fit object.</dd>

 <dt>type</dt>
<dd>Level of the model for which to calculate VIFs (for example,
 <code>'state'</code>)</dd>

</dl>

Compute Variance Inflation Factors for an unmarkedFit Object.

vif: Compute Variance Inflation Factors for an unmarkedFit Object.

Description

Usage

Value

Arguments