Example SDE models.

Provides sample C++ code for several SDE models.

sde.examples(
  model = c("hest", "pgnet", "lotvol", "biou", "eou"),
  file.only = FALSE
)

Arguments

model	Character string giving the name of a sample model. Possible values are: hest, pgnet, lotvol, biou, eou. See Details.
file.only	If TRUE returns only the path to the header file containing the sdeModel object implementation.

Value

An sde.model object, or the path to the C++ model header file.

Details

All pre-compiled models are with the default prior and with OpenMP disabled. A full description of the example models can be found in the package vignette; to view it run vignette("msde-exmodels").

See also

sde.make.model() for sde.model objects, mvn.hyper.check() for specification of the default prior.

Examples

# Heston's model
hmod <- sde.examples("hest") # load pre-compiled model

# inspect model's C++ code
hfile <- sde.examples("hest", file.only = TRUE)
cat(readLines(hfile), sep = "\n")
#> /// @file hestModel.h
#> 
#> #ifndef hestModel_h
#> #define hestModel_h 1
#> 
#> /// SDE model class for Heston's stochastic volatility model.
#> ///
#> /// The model is given by
#> /// ```
#> /// dXt = (alpha - .125 * Zt^2)dt + .5 * Zt dB_Xt
#> /// dZt = (beta/Zt - .5*gamma * Zt)dt + sigma * dB_Zt
#> /// cor(B_Xt, B_Zt) = rho
#> /// ```
#> ///
#> /// The data vector is `x = (X, Z)` and the parameter vector is `theta = (alpha, gamma, beta, sigma, rho)`.
#> class sdeModel {
#>  public:
#>   static const int nParams = 5; ///< Number of model parameters.
#>   static const int nDims = 2; ///< Number of SDE dimensions.
#>   static const bool sdDiff = true; ///< Diffusion is on the standard deviation scale.
#>   static const bool diagDiff = false; ///< Diffusion is not diagonal.
#>   /// SDE drift function.
#>   void sdeDr(double *dr, double *x, double *theta);
#>   /// SDE diffusion function.
#>   void sdeDf(double *df, double *x, double *theta);
#>   /// SDE data validator.
#>   bool isValidData(double *x, double *theta);
#>   /// SDE parameter validator.
#>   bool isValidParams(double *theta);
#> };
#> 
#> /// @param[out] dr Array into which to store the calculated drift.
#> /// @param[in] x Array of SDE components at a given time point.
#> /// @param[in] theta Array of SDE parameters.
#> inline void sdeModel::sdeDr(double *dr, double *x, double *theta) {
#>   dr[0] = (theta[0] - .125 * x[1]*x[1]); // x
#>   dr[1] = (theta[2]/x[1] - .5 * theta[1]*x[1]); // z
#>   return;
#> }
#> 
#> /// @param[out] df Array into which to store the calculated diffusion matrix.
#> /// @param[in] x Array of SDE components at a given time point.
#> /// @param[in] theta Array of SDE parameters.
#> inline void sdeModel::sdeDf(double *df, double *x, double *theta) {
#>   df[0] = .5 * x[1];
#>   df[2] = theta[3];
#>   df[3] = sqrt(1.0-theta[4]*theta[4]) * df[2];
#>   df[2] *= theta[4];
#>   return;
#> }
#> 
#> /// @param[in] x Array of SDE components at a given time point.
#> /// @param[in] theta Array of SDE parameters.
#> ///
#> /// @return Whether or not the SDE data `x` is valid.  In this case we must have `Zt > 0`.
#> inline bool sdeModel::isValidData(double *x, double *theta) {
#>   return(x[1] > 0.0);
#> }
#> 
#> /// @param[in] theta Array of SDE parameters.
#> ///
#> /// @return Whether or not the SDE parameters `theta` are valid.  In this case we must have `gamma, sigma > 0`, `beta > sigma^2/2`, and `|rho| < 1`.
#> inline bool sdeModel::isValidParams(double *theta) {
#>   bool isValid;
#>   isValid = (theta[1] > 0) && (theta[3] > 0);
#>   isValid = isValid && (-1.0 < theta[4]) && (1.0 > theta[4]);
#>   isValid = isValid && (theta[2] > 0.5 * theta[3] * theta[3]);
#>   return(isValid);
#> }
#> 
#> #endif

if (FALSE) {
# compile it from scratch
param.names <- c("alpha", "gamma", "beta", "sigma", "rho")
data.names <- c("X", "Z")
hmod <- sde.make.model(ModelFile = hfile,
                       param.names = param.names,
                       data.names = data.names)
}