bin_t: Create a binary exposure trend vector

In eesim: Simulate and Evaluate Time Series for Environmental Epidemiology

Description

Creates a trend vector for binary exposure data, centered at a probability p.

Usage

bin_t(n, p, trend = "no trend", slope = 1, amp = 0.01,
  start.date = "2000-01-01", custom_func = NULL, ...)

Arguments

n	A non-negative integer specifying the number of days to simulate.
p	A numeric value between 0 and 1 giving the mean probability of exposure across study days.
trend	A character string that gives the trend function to use. 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. "monthly": Uses a user-specified probability of exposure for each month.
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 -.5 and .5.
start.date	A date of the format "yyyy-mm-dd" from which to begin simulating values.
custom_func	An R object specifying a customized function from which to create a trend variable. Must accept arguments n and p.
...	Optional arguments to a custom trend function

Value

A numeric vector of daily expected probability of exposure, to be used to generate binary exposure data with seasonal trends.

Examples

bin_t(n = 5, p = .3, trend = "cos1", amp = .3)

eesim documentation built on May 2, 2019, 7:30 a.m.