Market data and model simulation functionality based on the data generating process induced by the market model specifications.
simulate_data
Returns a data tibble
with simulated data from a generating process that
matches the passed model string. By default, the simulated observations of the
controls are drawn from a normal distribution.
simulate_model
Simulates a data tibble
based on the generating process of the passed model
and uses it to initialize a model object. Data are simulated using the
simulate_data
function.
simulate_data( model_type_string, nobs = NA_integer_, tobs = NA_integer_, alpha_d = NA_real_, beta_d0 = NA_real_, beta_d = NA_real_, eta_d = NA_real_, alpha_s = NA_real_, beta_s0 = NA_real_, beta_s = NA_real_, eta_s = NA_real_, gamma = NA_real_, beta_p0 = NA_real_, beta_p = NA_real_, sigma_d = 1, sigma_s = 1, sigma_p = 1, rho_ds = 0, rho_dp = 0, rho_sp = 0, seed = NA_integer_, price_generator = function(n) stats::rnorm(n = n, mean = 2.5, sd = 0.5), control_generator = function(n) stats::rnorm(n = n, mean = 2.5, sd = 0.5), verbose = 0 ) # S4 method for ANY simulate_data( model_type_string, nobs = NA_integer_, tobs = NA_integer_, alpha_d = NA_real_, beta_d0 = NA_real_, beta_d = NA_real_, eta_d = NA_real_, alpha_s = NA_real_, beta_s0 = NA_real_, beta_s = NA_real_, eta_s = NA_real_, gamma = NA_real_, beta_p0 = NA_real_, beta_p = NA_real_, sigma_d = 1, sigma_s = 1, sigma_p = 1, rho_ds = 0, rho_dp = 0, rho_sp = 0, seed = NA_integer_, price_generator = function(n) stats::rnorm(n = n, mean = 2.5, sd = 0.5), control_generator = function(n) stats::rnorm(n = n, mean = 2.5, sd = 0.5), verbose = 0 ) simulate_model( model_type_string, simulation_parameters, seed = NA, verbose = 0, ... ) # S4 method for ANY simulate_model( model_type_string, simulation_parameters, seed = NA, verbose = 0, ... )
model_type_string  Model type. It should be among 

nobs  Number of simulated entities. 
tobs  Number of simulated dates. 
alpha_d  Price coefficient of demand. 
beta_d0  Constant coefficient of demand. 
beta_d  Coefficients of exclusive demand controls. 
eta_d  Demand coefficients of common controls. 
alpha_s  Price coefficient of supply. 
beta_s0  Constant coefficient of supply. 
beta_s  Coefficients of exclusive supply controls. 
eta_s  Supply coefficients of common controls. 
gamma  Price equation's stability factor. 
beta_p0  Price equation's constant coefficient. 
beta_p  Price equation's control coefficients. 
sigma_d  Demand shock's standard deviation. 
sigma_s  Supply shock's standard deviation. 
sigma_p  Price equation shock's standard deviation. 
rho_ds  Demand and supply shocks' correlation coefficient. 
rho_dp  Demand and price shocks' correlation coefficient. 
rho_sp  Supply and price shocks' correlation coefficient. 
seed  Pseudo random number generator seed. 
price_generator  Pseudo random number generator callback for prices. The default generator is \(N(2.5, 0.25)\). 
control_generator  Pseudo random number generator callback for nonprice controls. The default generator is \(N(2.5, 0.25)\). 
verbose  Verbosity level. 
simulation_parameters  List of parameters used in model simulation. See the

...  Additional parameters to be passed to the model's constructor. 
simulate_data
: The simulated data.
simulate_model
: The simulated model.
simulate_data
: Simulate model data.
simulate_model
: Simulate model.