Plot_func

Draw the diagram of differential equation

Use numerical optimization to fit ordinary differential equations (ODEs) to time series data to examine the dynamic relationships between variables or the characteristics of a dynamical system. It can now be used to estimate the parameters of ODEs up to second order, and can also apply to multilevel systems. See <https://github.com/yueqinhu/defit> for details.

Yueqin Hu

deFit

Fitting Differential Equations to Time Series Data

Qingshan Liu

Minglan Li

Plot_func function

<dl><dt>userdata</dt>
<dd>a data frame containing all model variables. The "time" column must be included.</dd>
<dt>predict</dt>
<dd>predict data.</dd>
<dt>modelDF</dt>
<dd>a dataframe of full model.</dd>
<dt>var_model</dt>
<dd>a dataframe containing equations.</dd>
<dt>field_model</dt>
<dd>the user's data columns.</dd>
<dt>order_model</dt>
<dd>N-order differential equation.</dd>
<dt>multi_model</dt>
<dd>TRUE or FALSE</dd></dl>

Arguments

Draw the diagram of differential equation — Plot_func

<dl>

<dt>userdata</dt>
<dd>a data frame containing all model variables. The "time" column must be included.</dd>


<dt>predict</dt>
<dd>predict data.</dd>


<dt>modelDF</dt>
<dd>a dataframe of full model.</dd>


<dt>var_model</dt>
<dd>a dataframe containing equations.</dd>


<dt>field_model</dt>
<dd>the user's data columns.</dd>


<dt>order_model</dt>
<dd>N-order differential equation.</dd>


<dt>multi_model</dt>
<dd>TRUE or FALSE</dd>

</dl>

Plot_func: Draw the diagram of differential equation

Description

Usage

Value

Arguments