sim_exposure: Simulate time series of exposure values
In eesim: Simulate and Evaluate Time Series for Environmental Epidemiology

Description Usage Arguments Value Examples

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.

sim_exposure(n, central = NULL, sd = NULL, trend = "no trend",
  slope = 1, amp = 0.6, exposure_type = NULL, start.date = "2001-01-01",
  cust_exp_func = NULL, cust_exp_args = NULL, cust_expdraw = NULL,
  cust_expdraw_args = list())

`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 `trend = "linear"` or `trend = "cos1linear"`.
`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 `n` and `prob` for a binary exposure function and inputs `n` and `mean` for a continuous exposure function. The custom function must output a vector of simulated exposure values.
`cust_expdraw_args`	A list of arguments other than `n` required by the `cust_expdraw` function.

A data frame with two columns: date (date) and simulated exposure values (x).

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()

        date x
1 2001-01-01 0
2 2001-01-02 0
3 2001-01-03 0
4 2001-01-04 1
5 2001-01-05 0
        date         x
1 2001-01-01  87.70073
2 2001-01-02  90.18196
3 2001-01-03  92.27814
4 2001-01-04 128.57696
5 2001-01-05 101.85581