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deFit (version 0.3.0)

Fitting Differential Equations to Time Series Data

Description

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 for details.

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Version

Install

install.packages('deFit')

Monthly Downloads

166

Version

0.3.0

License

GPL (>= 3)

Maintainer

Yueqin Hu

Last Published

October 18th, 2024

Functions in deFit (0.3.0)

example2

Bivariate first-order differential equation
Init_func

Initialize model Judgement variables and so on.
Info_func

Calculate R-squared RMSE SE and so on.
Solver_BiFirst_func

Solver of bivariate first-order differential equation
Solver_MultiUniSecond_func

Solver of Multilevel univariate second-order differential equation
calcDerivatives

Calculating the Derivatives
Plot_func

Draw the diagram of differential equation
Scale_within

Center the data according to model
Solver_UniSecond_func

Solver of univariate second-order differential equation
Solver_MultiBiFirst_func

Solver of Multilevel bivariate first-order differential equation
defit

Fitting Differential Equations to Time Series Data
example4

Bivariate first-order differential equation
example1

Univariate second-order differential equation
example3

University of Michigan consumer sentiment index