Description Usage Arguments Value Examples

View source: R/customizable_functions.R

Simulates a time series of binary or continuous exposure values with or without seasonal trends. It also allows the user to use a custom function for the shape of the exposure trend.

1 2 3 4 |

`n` |
A non-negative integer specifying the number of days to simulate. |

`central` |
A numeric value specifying the mean probability of exposure (for binary data) or the mean exposure value (for continuous data). |

`sd` |
A numeric value giving the standard deviation of the exposure values from the exposure trend line. |

`trend` |
A character string that specifies the desired trend function. Options are: "no trend": No trend, either seasonal or long-term (default). "cos1": A seasonal trend only. "cos2": A seasonal trend with variable amplitude across years. "cos3": A seasonal trend with steadily decreasing amplitude over time. "linear": A linear long-term trend with no seasonal trend. "curvilinear": A curved long-term trend with no seasonal trend. "cos1linear": A seasonal trend plus a linear long-term trend.
See the package vignette for examples of the shapes of these trends. |

`slope` |
A numeric value specifying the slope of the trend, to be used
with |

`amp` |
A numeric value specifying the amplitude of the seasonal trend. Must be between -1 and 1. |

`exposure_type` |
A character string specifying the type of exposure. Choices are "binary" or "continuous". |

`start.date` |
A date of the format "yyyy-mm-dd" from which to begin simulating daily exposures |

`cust_exp_func` |
An R object specifying the function to use to generate custom exposure values. |

`cust_exp_args` |
A list of arguments used in the user-specified custom function. |

`cust_expdraw` |
An R object specifying a user-created function
which determines the distribution of random noise off of the trend line.
This function must have inputs |

`cust_expdraw_args` |
A list of arguments other than |

A data frame with two columns: date (`date`

) and simulated
exposure values (`x`

).

1 2 3 4 5 6 7 8 9 10 | ```
sim_exposure(n = 5, central = 0.25, exposure_type = "binary")
sim_exposure(n = 5, central = 100, sd = 10, exposure_type = "continuous")
library(ggplot2)
x_cont <- sim_exposure(n = 1000, central = 100, sd = 10,
exposure_type = "continuous",
trend = "cos1linear", amp = 0.6)
ggplot(x_cont, aes(x = date, y = x)) + geom_point()
x_cust <- sim_exposure(n = 1000, cust_exp_func = "custom_exposure",
cust_exp_args = list(metric = "temp"))
ggplot(x_cust, aes(x = date, y = x)) + geom_point()
``` |

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