Creating Flow of Brownian Motion (by a Random Walk)
Adjustment By Beta Distribution
Empirical Covariance for Brownian Motion
Simulation of Diffusion Processes.
Simulation M-Samples of Random Variable X(v[t]) For A Simulated Diffusion Process
Histograms of Random Variable X
Creating Brownian Bridge Model
Creating Constant Elasticity of Variance (CEV) Models (by Milstein Scheme)
Simulation Three-Dimensional Brownian Motion (by the Normal Distribution)
Properties of the stochastic integral and Ito Process [2]
Adjustment By Log Normal Distribution
Simulation Three-Dimensional Brownian Motion (by a Random Walk)
Creating Flow of Brownian Bridge Model
Creating The Chan-Karolyi-Longstaff-Sanders (CKLS) family of models (by Milstein Scheme)
Observation of Ornstein-Uhlenbeck Process
Kernel Density of Random Variable X
Properties of the stochastic integral and Ito Process [1]
Simulation The First Passage Time FPT For A Simulated Diffusion Process
Creating Flow of Brownian Motion (by the Normal Distribution)
Simulation The First Passage Time FPT For Attractive Model(S >= 2,Sigma)
Kolmogorov-Smirnov Tests (F Distribution)
Creating Flow of Hull-White/Vasicek (HWV) Gaussian Diffusion Models
Creating Flow of Ornstein-Uhlenbeck Process
Three-Dimensional Attractive Model Model(S >= 2,Sigma)
Adjustment the Empirical Distribution of Random Variable X
Adjustment By Normal Distribution
Creating The General Hyperbolic Diffusion (by Milstein Scheme)
Simulation Two-Dimensional Brownian Motion (by the Normal Distribution)
Simulation Two-Dimensional Brownian Motion (by a Random Walk)
Parametric Estimation of Hull-White/Vasicek (HWV) Gaussian Diffusion Models(Exact likelihood inference)
Creating Stochastic Process The Student Distribution
Creating The modified CIR and hyperbolic Process (by Milstein Scheme)
Creating Brownian Motion Model (by the Normal Distribution)
Display a Data Frame in a Tk Text Widget
Creating Geometric Brownian Motion (GBM) Models
Creating Pearson Diffusions Process (by Milstein Scheme)
Radial Process Model(S = 1,Sigma) Or Attractive Model
Adjustment By Gamma Distribution
Stratonovitch Integral [4]
Simulation The First Passage Time FPT For Attractive Model for Two-Diffusion Processes V(1) and V(2)
Brownian Motion Property (Invariance by reversal of time)
Creating Random Walk
Creating Radial Ornstein-Uhlenbeck Process (by Milstein Scheme)
Kolmogorov-Smirnov Tests (Exponential Distribution)
Calculating the Empirical Distribution of Random Variable X
Parametric Estimation of Ornstein-Uhlenbeck Model (Explicit Estimators)
Stratonovitch Integral [3]
Kolmogorov-Smirnov Tests (Weibull Distribution)
Radial Process Model(S >= 2,Sigma) Or Attractive Model
Creating Double-Well Potential Model (by Milstein Scheme)
Creating Hull-White/Vasicek (HWV) Gaussian Diffusion Models
Approximated Conditional Law a Diffusion Process
Two-Dimensional Attractive Model for Two-Diffusion Processes V(1) and V(2)
Properties of the stochastic integral and Ito Process [4]
Kolmogorov-Smirnov Tests (Chi-Squared Distribution)
Adjustment By Exponential Distribution
Parametric Estimation of Arithmetic Brownian Motion(Exact likelihood inference)
Kolmogorov-Smirnov Tests (Student t Distribution)
Evolution a Telegraphic Process in Time
Creating Brownian Motion Model (by a Random Walk)
Kolmogorov-Smirnov Tests (Gamma Distribution)
Adjustment By Weibull Distribution
Creating Bessel process (by Milstein Scheme)
Brownian Motion Property
Properties of the stochastic integral and Ito Process [5]
Creating Ornstein-Uhlenbeck Process
Stratonovitch Integral [2]
Kolmogorov-Smirnov Tests (Log Normal Distribution)
Creating Arithmetic Brownian Motion Model
Adjustment the Density of Random Variable by Kernel Methods
Creating The Jacobi Diffusion Process (by Milstein Scheme)
Two-Dimensional Attractive Model Model(S = 1,Sigma)
Creating Diffusion Bridge Models (by Euler Scheme)
Three-Dimensional Attractive Model Model(S = 1,Sigma)
Parametric Estimation of Model Black-Scholes (Exact likelihood inference)
Numerical Solution of Two-Dimensional SDE
Three-Dimensional Attractive Model for Two-Diffusion Processes V(1) and V(2)
Two-Dimensional Attractive Model Model(S >= 2,Sigma)
Predictor-Corrector Method For Three-Dimensional SDE
Creating Stochastic Process The Gamma Distribution
Two-Dimensional Attractive Model in Polar Coordinates Model(S >= 2,Sigma)
Parametric Estimation of Ornstein-Uhlenbeck Model (Exact likelihood inference)
Adjustment By Student t Distribution
Numerical Solution of Three-Dimensional SDE
Stratonovitch Integral [1]
Two-Dimensional Attractive Model in Polar Coordinates Model(S = 1,Sigma)
Kolmogorov-Smirnov Tests (Beta Distribution)
Observation of Arithmetic Brownian Motion
Observation of Geometric Brownian Motion Model
Creating The Hyperbolic Process (by Milstein Scheme)
Predictor-Corrector Method For One-Dimensional SDE
Kolmogorov-Smirnov Tests (Normal Distribution)
Numerical Solution of One-Dimensional SDE
Realization a Telegraphic Process
Creating White Noise Gaussian
Predictor-Corrector Method For Two-Dimensional SDE
Creating Flow of The Arithmetic Brownian Motion Model
Adjustment By Chi-Squared Distribution
Creating Flow of Geometric Brownian Motion Models
Adjustment By F Distribution
Brownian Motion Property (trajectories brownian between function (+/-)2*sqrt(C*t))
Adjustment the Density of Random Variable X by Histograms Methods
Creating Cox-Ingersoll-Ross (CIR) Square Root Diffusion Models (by Milstein Scheme)
Properties of the stochastic integral and Ito Process [3]
Creating The Exponential Martingales Process
Brownian Motion Property (Invariance by scaling)
Simulation The First Passage Time FPT For Attractive Model(S = 1,Sigma)
Creating Ahn and Gao model or Inverse of Feller Square Root Models (by Milstein Scheme)