feat: stabalize variance gamma

README.md

@@ -21,6 +21,8 @@ Minimal documentation is available at [stochastic-rs](https://docs.rs/stochastic
 - [x] Cox-Ingersoll-Ross process
 - [x] Ornstein-Uhlenbeck process
 - [x] Jacobi process
+- [x] Variance Gamma model
+
 
 # Stochastic models
 - [x] Heston model
@@ -55,7 +57,6 @@ Minimal documentation is available at [stochastic-rs](https://docs.rs/stochastic
 - [ ] Vasicek model
 - [ ] Duffie-Kan model
 - [ ] Jump-diffusion model
-- [ ] Variance Gamma model
 - [ ] Normal Inverse Gaussian model
 
 ## Future work

src/jumps/vg.rs

@@ -3,7 +3,6 @@ use ndarray::Array1;
 use rand::Rng;
 use rand_distr::Gamma;
 
-// TODO: under development
 pub fn vg(mu: f64, sigma: f64, nu: f64, n: usize, x0: Option<f64>, t: Option<f64>) -> Vec<f64> {
   let dt = t.unwrap_or(1.0) / n as f64;
   let rng = rand::thread_rng();