Description Usage Arguments Details Value Examples

View source: R/methods-for-data-generation.R

Method for generating a sampling design for data generation following a random effects meta regression model with known heteroscedasticity.

1 | ```
designY(n, h_bounds, d_bounds, x)
``` |

`n` |
resolution of the heterogeneity and heteroscedasticity parameters, i.e. the number of of different (heterogeneity, heteroscedasticity) pairs in the design. |

`h_bounds` |
bounds of the heterogeneity. |

`d_bounds` |
bounds of the heteroscedasticity. |

`x` |
design matrix. |

Generates a sampling design for the heterogeneity 'h' and a heteroscedasticity 'd1', ..., 'dk'.

Points in the design are selected via a maxi-min hypercube sampling using the 'lhs' package in a predefined parameter cube.

Function returns a data frame. Each line of this data frame can be an input to the function 'rY' which is used to sample data from such a design.

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