WebCab Mathematical EJB Components

   WebCab Probability and Statistics Suite v3.1

This suite consists of four EJB modules: Statistics, Discrete Probability, Standard Proability Distributions, Confidence Intervals and Hypothesis Testing which offer the following functionality...

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   WebCab Correlation and Regression v4.0

The Correlation and Regression EJB component allows the user to investigate relationships between two or more variables and then use these findings to predict one variable from the given values of other variables. We cover linear (Pearman's, t-test, z-transform) and rank (Spearman's, Kendall's) correlation, linear regression and conditional means.

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   WebCab Ordinary Differential Equations v4.0

WebCab ODE implements methods for finding solutions to systems of ordinary differential equations (ODE's) using Runge Kutta, modified mid-point, Bulirsh-Stoer, Rosenbrock, semi-implicit extrapolation methods and the second-order conservative equations.

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   WebCab Confidence Intervals and Hypothesis Testing v1.5

Within this component we present two aspects of inferential statistics known as confidence intervals and hypothesis testing. Confidence intervals determine the level of confidence in pointwise statistics (e.g. mean, variance) of the sample in relation to the statistics for the entire population. With hypothesis testing the user can judge which of several hypotheses sampled evidence best supports.

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   WebCab Interpolation and Extrapolation

We offer computationally convenient and effective schemes of interpolation and extrapolation. These methods are ideal for any system that needs to work with functions which are stored in tabular form. We include the methods of Newton polynomials, Lagrange's formula, Burlisch-Stoer algorithm, Cubic splines (natural and free) and Bicubic interpolation. We also consider algorithms for nding the coefficients of an interpolating function and interpolation in higher dimensions.

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   WebCab Optimization v2.5

Solve complex one and multi dimensional optimizations problems efficiently with our powerful optimization component. This component offers advanced algorithms covering local and global unidimensional optimization, local multidimensional optimization with or without constraints. We also include a method for solving liner programming prooblems known as the simplex method.

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   WebCab Equation Solver v3.0

The WebCab Equation Solver Enterprise JavaBeans^TM component implements refined numerical procedures for solving equations in one space variable. We include Van Wijngaarden-Dekker-Brent algorithm, interval bisection method, secant and false position, Newton-Raphson method and Ridders' method. We implement local and Remote Method Invocation (RMI) equation delivery procedures.

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   WebCab Nummerical Differentation and Integration v4.0

WebCab Numerical Differentiation and Integration v4.0 Enterprise JavaBeans^TM component provides precise numerical techniques by which the definite integral and derivative of a function at a point can be evaluated. Ridders' algorithm, Newton polynomial and Chebyshev polynomial methods are used to approximate a functions derivative.

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WebCab Correlation and Regression v4.0
	The Correlation and Regression EJB component allows the user to investigate relationships between two or more variables and then use these findings to predict one variable from the given values of other variables. We cover linear (Pearman's, t-test, z-transform) and rank (Spearman's, Kendall's) correlation, linear regression and conditional means.
	<details> <buy>

WebCab Ordinary Differential Equations v4.0
	WebCab ODE implements methods for finding solutions to systems of ordinary differential equations (ODE's) using Runge Kutta, modified mid-point, Bulirsh-Stoer, Rosenbrock, semi-implicit extrapolation methods and the second-order conservative equations.
	<details> <buy>

WebCab Confidence Intervals and Hypothesis Testing v1.5
	Within this component we present two aspects of inferential statistics known as confidence intervals and hypothesis testing. Confidence intervals determine the level of confidence in pointwise statistics (e.g. mean, variance) of the sample in relation to the statistics for the entire population. With hypothesis testing the user can judge which of several hypotheses sampled evidence best supports.
	<details> <buy>

WebCab Interpolation and Extrapolation
	We offer computationally convenient and effective schemes of interpolation and extrapolation. These methods are ideal for any system that needs to work with functions which are stored in tabular form. We include the methods of Newton polynomials, Lagrange's formula, Burlisch-Stoer algorithm, Cubic splines (natural and free) and Bicubic interpolation. We also consider algorithms for nding the coefficients of an interpolating function and interpolation in higher dimensions.
	<details> <buy>

WebCab Optimization v2.5
	Solve complex one and multi dimensional optimizations problems efficiently with our powerful optimization component. This component offers advanced algorithms covering local and global unidimensional optimization, local multidimensional optimization with or without constraints. We also include a method for solving liner programming prooblems known as the simplex method.
	<details> <buy>

WebCab Equation Solver v3.0
	The WebCab Equation Solver Enterprise JavaBeans^TM component implements refined numerical procedures for solving equations in one space variable. We include Van Wijngaarden-Dekker-Brent algorithm, interval bisection method, secant and false position, Newton-Raphson method and Ridders' method. We implement local and Remote Method Invocation (RMI) equation delivery procedures.
	<details> <buy>

WebCab Nummerical Differentation and Integration v4.0
	WebCab Numerical Differentiation and Integration v4.0 Enterprise JavaBeans^TM component provides precise numerical techniques by which the definite integral and derivative of a function at a point can be evaluated. Ridders' algorithm, Newton polynomial and Chebyshev polynomial methods are used to approximate a functions derivative.
	<details> <buy>