Predict the exposure-response function at a new grid of points

1 2 3 4 |

`fit` |
An object containing the results returned by a the |

`y` |
a vector of outcome data of length |

`Z` |
an |

`X` |
an |

`z.pairs` |
data frame showing which pairs of pollutants to plot |

`method` |
method for obtaining posterior summaries at a vector of new points. Options are "approx" and "exact"; defaults to "approx", which is faster particularly for large datasets; see details |

`ngrid` |
number of grid points in each dimension |

`q.fixed` |
vector of quantiles at which to fix the remaining predictors in |

`sel` |
logical expression indicating samples to keep; defaults to keeping the second half of all samples |

`min.plot.dist` |
specifies a minimum distance that a new grid point needs to be from an observed data point in order to compute the prediction; points further than this will not be computed |

`center` |
flag for whether to scale the exposure-response function to have mean zero |

`z.names` |
optional vector of names for the columns of |

`verbose` |
TRUE or FALSE: flag of whether to print intermediate output to the screen |

`...` |
other argumentd to pass on to the prediction function |

For guided examples, go to https://jenfb.github.io/bkmr/overview.html

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

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