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