market_simulation: Market model simulation
In diseq: Estimation Methods for Markets in Equilibrium and Disequilibrium

market_simulation

R Documentation

Market model simulation

Description

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.

Usage

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),
  control_generator = function(n) stats::rnorm(n = n),
  verbose = 0
)

## S4 method for signature '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),
  control_generator = function(n) stats::rnorm(n = n),
  verbose = 0
)

simulate_model(
  model_type_string,
  simulation_parameters,
  seed = NA,
  verbose = 0,
  ...
)

## S4 method for signature 'ANY'
simulate_model(
  model_type_string,
  simulation_parameters,
  seed = NA,
  verbose = 0,
  ...
)

Arguments

`model_type_string`	Model type. It should be among `equilibrium_model`, `diseq_basic`, `diseq_directional`, `diseq_deterministic_adjustment`, and `diseq_stochastic_adjustment`.
`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 non-price controls. The default generator is N(2.5, 0.25).
`verbose`	Verbosity level.
`simulation_parameters`	List of parameters used in model simulation. See the `simulate_data` function for details.
`...`	Additional parameters to be passed to the model's constructor.