# plot.tpopt: Plot of Psi function for resulting design In rodd: Optimal Discriminating Designs

## Description

Plots the Psi(x,xi) function for resulting approximation xi^{**} of the T_P-optimal design achieved with the help of `tpopt`. The definition of Psi(x,xi) can be found in the “details” section of function's `tpopt` specifications.

## Usage

 ```1 2``` ```## S3 method for class 'tpopt' plot(x, ...) ```

## Arguments

 `x` an object of type "tpopt". `...` additional graphical parameters.

## Details

We are interested in the shape of function Psi(x,xi^{**}) when we want to ensure the convergence of the algorithm. If algorithm had converged, then support points of xi^{**} (which are represented by dots) will be near local maximums of the mentioned function. Furthermore, at all local maximums Psi(x,xi^{**}) should have the same value. Otherwise something went wrong and the algorithm should be restarted with another parameters.

`tpopt`, `summary.tpopt`, `print.tpopt`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34``` ```#List of models eta.1 = function(x, theta.1) theta.1[1] + theta.1[2] * x + theta.1[3] * (x ^ 2) + theta.1[4] * (x ^ 3) + theta.1[5] * (x ^ 4) eta.2 = function(x, theta.2) theta.2[1] + theta.2[2] * x + theta.2[3] * (x ^ 2) eta <- list(eta.1, eta.2) #List of fixed parameters theta.1 <- c(1,1,1,1,1) theta.2 <- c(1,1,1) theta.fix <- list(theta.1, theta.2) #Comparison table p <- matrix( c( 0, 1, 0, 0 ), c(length(eta), length(eta)), byrow = TRUE) x <- seq(-1, 1, 0.1) opt.1 <- list(method = 1, max.iter = 1) opt.2 <- list(method = 1, max.iter = 2) opt.3 <- list(method = 1) res.1 <- tpopt(x = x, eta = eta, theta.fix = theta.fix, p = p, opt = opt.1) res.2 <- tpopt(x = x, eta = eta, theta.fix = theta.fix, p = p, opt = opt.2) res.3 <- tpopt(x = x, eta = eta, theta.fix = theta.fix, p = p, opt = opt.3) plot(res.1) plot(res.2) plot(res.3) ```