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