estimate_one_timecourse_params_tf: Estimate One Timecourses Parameters

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

Estimate One Timecourses Parameters

Description

Estimate One Timecourses Parameters

Usage

estimate_one_timecourse_params_tf(
  one_timecourse,
  a_tc_id,
  use_prior,
  n_initializations,
  model,
  prior_pars = NULL,
  fit_intercept = FALSE,
  learning_rate = 0.1,
  n_iterations = 100,
  verbose = FALSE
)

Arguments

one_timecourse	dynamics of a single timecourse including time and abundance variables
a_tc_id	timecourse id for the timecourse being fit
use_prior	If FALSE, fit least squares. If TRUE, add priors for a MAP estimate.
n_initializations	Number of initializations to use for each timecourse.
model	model to fit: sigmoid one sigmoidal response impulse two sigmoidal responses
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
fit_intercept	If TRUE, the intercept will be fit, if FALSE, the intercept will be constrainted to zero
learning_rate	learning rate for the Adams optimizer
n_iterations	the number of iterations to run the optimizer
verbose	if TRUE then print additional information

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