Kernels (Math)

JIT-compiled solver kernels for numba-sde.

pyito.kernels.df_milstein_diagonal_all(drift_func, diffusion_func, args, y0, t0, dt, n_steps, n_paths, seed, epsilon=1e-05)

pyito.kernels.df_milstein_diagonal_final(drift_func, diffusion_func, args, y0, t0, dt, n_steps, n_paths, seed, epsilon=1e-05)

Derivative-Free Milstein for Diagonal noise.

pyito.kernels.df_milstein_scalar_all(drift_func, diffusion_func, args, y0, t0, dt, n_steps, n_paths, seed, epsilon=1e-05)

pyito.kernels.df_milstein_scalar_final(drift_func, diffusion_func, args, y0, t0, dt, n_steps, n_paths, seed, epsilon=1e-05)

pyito.kernels.euler_maruyama_correlated_all(drift_func, diffusion_func, args, y0, t0, dt, n_steps, n_paths, seed)

pyito.kernels.euler_maruyama_correlated_final(drift_func, diffusion_func, args, y0, t0, dt, n_steps, n_paths, seed)

pyito.kernels.euler_maruyama_diagonal_all(drift_func, diffusion_func, args, y0, t0, dt, n_steps, n_paths, seed)

pyito.kernels.euler_maruyama_diagonal_final(drift_func, diffusion_func, args, y0, t0, dt, n_steps, n_paths, seed)

pyito.kernels.euler_maruyama_scalar_all(drift_func, diffusion_func, args, y0, t0, dt, n_steps, n_paths, seed)

pyito.kernels.euler_maruyama_scalar_final(drift_func, diffusion_func, args, y0, t0, dt, n_steps, n_paths, seed)

pyito.kernels.milstein_diagonal_all(drift_func, diffusion_func, diffusion_deriv_func, args, y0, t0, dt, n_steps, n_paths, seed)

pyito.kernels.milstein_diagonal_final(drift_func, diffusion_func, diffusion_deriv_func, args, y0, t0, dt, n_steps, n_paths, seed)

Milstein method for Diagonal noise (independent dW per dimension).

pyito.kernels.milstein_scalar_all(drift_func, diffusion_func, diffusion_deriv_func, args, y0, t0, dt, n_steps, n_paths, seed)

pyito.kernels.milstein_scalar_final(drift_func, diffusion_func, diffusion_deriv_func, args, y0, t0, dt, n_steps, n_paths, seed)