Description Usage Arguments Value Author(s)

Plots a standard error estimate of thetahat (slope over intercept) over a range of possible theta0 values in order to investigate robustness of the the initial theta0 guess.

1 2 3 4 |

`n` |
The number of experimental runs. |

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

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

`theta` |
The putative true value. This is used to see how much efficiency given up by designing it for |

`theta0_min` |
Simulating over different guesses of theta0, this is the minimum guess. |

`theta0_max` |
Simulating over different guesses of theta0, this is the maximum guess. |

`theta0` |
The guess used to construct the experimental design. Specify only if you wish to see this
value plotted. Default is |

`beta0` |
A guess to be used for the intercept. Defaults to |

`sigma` |
A guess to be used for the homoskedastic variance of the measurement errors. If known accurately,
then the standard errors (i.e. the y-axis on the plot) will be accurate. Otherwise, the standard
errors are useful only when compared to each other in a relative sense. Defaults to |

`RES` |
The number of points on the x-axis to simulate. Higher numbers will give smoother results. Default is |

`Nsim` |
The number of models to be simulated for estimating the standard error at each value on the x-axis. Default is |

`error_est` |
The error metric for the estimates. The sample standard deviation (i.e. |

`theta_logged` |
Should the values of theta be logged? Default is |

`error_pct` |
Plot error as a percentage increase from minimum. Default is |

`plot_rhos` |
Plot an additional graph of rho by theta0. Default is |

`...` |
Additional arguments passed to the |

A list with original parameters as well as data from the simulation

Adam Kapelner

optDesignSlopeInt documentation built on May 29, 2017, 11:19 p.m.

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