phaseportmod: Phase Potrait with Modeled Trajectories for Specified...
In bdynsys: Bayesian Dynamical System Model

Description Usage Arguments Author(s) Examples

phaseportmod creates a phase portrait (velocity plot, vectorfield) based on the two differential equations that were considered to be the overall best models for indicator 1 and indicator 2. The user may specify entities for which he/she wants to obtain the predicted (modeled) trajectories over the phase portrait. The user may extend the period of time for the modeling to get future-predicted trjectories of the entities based on the models. It calls the function preprocess_data. It requires the packages plm, pracma, deSolve and graphics. The function produces graphs by some default settings. For specific requirements the user might want to modify the code according to his/her needs.

1 2	phaseportmod(dataset, yearnr, xv, yv, rangeX, rangeY, param, f, entidx1, entidx2, entidx3, entidx4, entidx5, entidx6)

`dataset`	a `plm` `pdata.frame` panel data frame.
`yearnr`	number of years for which the user wants to produce the phase portrait and obtain the modeled trajectories of the specified entities.
`xv`	a reference to variable from the paneldata to be included as indicator 1 in the modeling procedure.
`yv`	a reference to variable from the paneldata to be included as indicator 2 in the modeling procedure.
`rangeX`	defines the range of the indicator 1.
`rangeY`	defines the range of the indicator 2.
`param`	a vector with parameters from the two models in f.
`f`	a function that contains the models of the two indicators.
`entidx1`	index of an entity in the wide format data of a variable.
`entidx2`	index of an entity in the wide format data of a variable.
`entidx3`	index of an entity in the wide format data of a variable.
`entidx4`	index of an entity in the wide format data of a variable.
`entidx5`	index of an entity in the wide format data of a variable.
`entidx6`	index of an entity in the wide format data of a variable.

Viktoria Spaiser: viktoria.sp@web.de

## Phase Portrait with Model Trajectories over 30 years with the following two models:
## dx/dt  = 0.014 + 0.0064*x*y - 0.02*x and dy/dt = 0.106*x^3 - 0.062*y/x

phaseportmod(datap, 30, datap$logGDP, datap$DemocrH, seq(0, 1, by = 0.01), seq(0, 1, by = 0.01),
param <- c(0.014, -0.0064, -0.02, 0.106, -0.062), f <- function(t,Y=c()) 
rbind(0.014 + 0.0064*Y[1]*Y[2] - 0.02*Y[1], 0.106*Y[1]^3 - 0.062*(Y[2]/Y[1])), 1, 2, 4, 5, 7, 9)