Insert GLM Time Variation

Usage

mp_tmb_insert_glm_timevar(
  model,
  parameter_name,
  design_matrix,
  timevar_coef,
  link_function = mp_log,
  matrix_coef_name = sprintf("matrix_coef_%s", parameter_name),
  matrix_row_name = sprintf("matrix_row_%s", parameter_name),
  matrix_col_name = sprintf("matrix_col_%s", parameter_name),
  linear_pred_name = sprintf("linear_pred_%s", parameter_name),
  timeseries_name = sprintf("timeseries_%s", parameter_name),
  timevar_coef_name = sprintf("time_var_%s", parameter_name),
  time_index_name = sprintf("time_index_%s", parameter_name),
  sparsity_tolerance = 0,
  engine_function = c("sparse_mat_mult", "group_sums")
)

Arguments

model: A model specification (see mp_tmb_model_spec).
parameter_name: Character string giving the name of the parameter to make time-varying.
design_matrix: Matrix of time variation.
timevar_coef: Initial coefficient matrix with the same number of rows as there are columns of the design_matrix.
link_function: Link function given by functions like mp_log.
matrix_coef_name: Name of the vector containing values of the non-zero elements of the design matrix.
matrix_row_name: Name of the vector containing row indices of the non-zero elements of the design matrix.
matrix_col_name: Name of the vector containing column indices of the non-zero elements of the design matrix.
linear_pred_name: Name of the vector containing the linear predictor.
timeseries_name: Name of the vector containing the time-series of the varying parameter.
timevar_coef_name: Name of the vector containing the time-varying parameter coefficients.
time_index_name: Name of the index at which the time varying parameter changes.
sparsity_tolerance: Make design matrix coefficients exactly zero when they are below this tolerance.
engine_function: Which of two engine_functions, sparse_mat_mult or group_sums, should be used to compute the matrix multiplication. The only reason to use anything other than the default is for back-compatibility with an existing script.