oed_for_slope_over_intercept | R Documentation |

Create an optimal design for measuring the slope divided by the intercept

```
oed_for_slope_over_intercept(
n,
xmin,
xmax,
theta0,
f_hetero = NULL,
MaxIter = 6000,
MaxFunEvals = 6000,
TolFun = 1e-06,
NUM_RAND_STARTS = 50
)
```

`n` |
The number of experimental runs. |

`xmin` |
The minimum value of the independent variable. |

`xmax` |
The maximum value of the independent variable. |

`theta0` |
The guess of the true value of the slope / intercept. |

`f_hetero` |
Specification of heteroskedasticity: the h(x) which relates the value of the
independent variable to the variance in the response around the line at that place
or the proportional variance at that point. If |

`MaxIter` |
For the heteroskedastic design, a Nelder-Mead search is used (via the function |

`MaxFunEvals` |
For the heteroskedastic design, a Nelder-Mead search is used (via the function |

`TolFun` |
For the heteroskedastic design, a Nelder-Mead search is used (via the function |

`NUM_RAND_STARTS` |
For the heteroskedastic design, a Nelder-Mead search is used (via the function |

An n-vector of x-values which specifies the optimal design

Adam Kapelner

```
xmin = 5 / 15
xmax = 19 / 1
n = 10
theta0 = 0.053
opt_homo_design = oed_for_slope_over_intercept(n, xmin, xmax, theta0)
table(opt_homo_design)
```

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