simulate_timecourses: Simulate timecourses

In calico/impulse: Fit Impulse and Sigmoidal Curves to Longitudinal Data Using TensorFlow

Simulate timecourses

Description

Simulate timecourses

Usage

simulate_timecourses(
  n,
  Pr_impulse = 0.5,
  timepts = seq(0, 120, by = 5),
  prior_pars = c(v_sd = 1.2, rate_shape = 2, rate_scale = 0.25, time_shape = 1,
    time_scale = 30),
  measurement_sd = 0.2,
  observation_level_noise = 0
)

Arguments

n	number of timecourses to
Pr_impulse	probability of an impulse (versus a sigmoid)
timepts	a numeric vector of timepoints to fit
prior_pars	Named numeric vector of parameters to use for priors (if use_prior is TRUE) v_sd Gaussian SD of assymptotes (v_inter and v_final) rate_shape Shape of rate Gamma rate_scale Scale of rate Gamma time_shape Shape of t_rise and t_fall - t_rise Gamma time_scale Scale of t_rise and t_fall - t_rise Gamma
measurement_sd	gaussian measurement noise to add
observation_level_noise	scale samples by exp(rnorm(1)*observation_level_noise) to introduce samples with varying noise levels. Set a zero by default for a homoschedastic model.

Examples

simulate_timecourses(n = 20)

calico/impulse documentation built on June 4, 2024, 5:28 a.m.