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