predictors

A data frame of input data to be used in as predictor values in transition
functions.

Code to specify, run, and then visualize and analyze the results of
Ixodidae (hard-bodied ticks) population and infection dynamics models. Such
models exist in the literature, but the source code to run them is not
always available. 'IxPopDyMod' provides an easy way for these models to be
written and shared.

Myles Stokowski

IxPopDyMod

Framework for Tick Population and Infection Modeling

David Allen

predictors function

<dl><dt>df</dt>
<dd>input data frame, with columns:<dl>
<dt>pred</dt>
<dd>String specifying the name of the predictor, e.g. "temp" or
"host_den"</dd></dl></dd><dt>pred_subcategory</dt>
<dd>This column allows specifying predictors for which
there are multiple values for a given j_day. Predictor values are sorted by
this column in the config set up. This ensures that when accessing a
predictor with multiple values for the same j_day, we get a vector of
predictor values ordered by this column. A typical use for this column is
to specify the host density of each host species.</dd><dt>j_day</dt>
<dd>Integer specifying the Julian day, or NA for predictors with
constant value over time</dd><dt>value</dt>
<dd>Numeric value of predictor</dd>
</dl>
<dt>verbose</dt>
<dd>Boolean; whether to warn about reordering the <code>df</code></dd>

Arguments

Create a table of predictors — predictors

<dl>

<dt>df</dt>
<dd>input data frame, with columns:<dl>
<dt>pred</dt>
<dd>String specifying the name of the predictor, e.g. "temp" or
"host_den"</dd>

<dt>pred_subcategory</dt>
<dd>This column allows specifying predictors for which
there are multiple values for a given j_day. Predictor values are sorted by
this column in the config set up. This ensures that when accessing a
predictor with multiple values for the same j_day, we get a vector of
predictor values ordered by this column. A typical use for this column is
to specify the host density of each host species.</dd>

<dt>j_day</dt>
<dd>Integer specifying the Julian day, or NA for predictors with
constant value over time</dd>

<dt>value</dt>
<dd>Numeric value of predictor</dd>


</dl></dd>


<dt>verbose</dt>
<dd>Boolean; whether to warn about reordering the <code>df</code></dd>

</dl>

predictors: Create a table of `predictors`

Description

Usage

Value

Arguments