VMath ActiveX DLL 2.0
  This ActiveX DLL is developed for developers and integrated most algorithmns of Visual Stats, Visual Fitting, Visual Probability, Visual Optim, Visual Matrix and many other numeric algorithmns. This DLL can be used in any development enviroment supporting COM DLL such as VC, VB, Excel, Access etc.  
 

The main features of VMath ActiveX DLL 2.0

 
  Statistics Analysis

Probability Distributions
    Probability density function (PDF)
    Cumulative distribution function (CDF)
    Inverse cumulative distribution function(Percentile)
    Parameter estimation
    Mean, variance
  of the following distributions
    Bernoulli distribution
    Beta distribution
    Binomial distribution
    Cauchy distribution
    Chi-squared distribution
    Exponential distribution
    F distribution
    Gamma distribution
    Geometric distribution
    Hypergeometric distribution
    Lognormal distribution
    Normal distribution
    Poisson distribution
    Rayleigh distribution
    T distribution
    Uniform distribution
    Weibull distribution
Outlier Test
    Romanovsky test(t test)
    Dixon test
    Grubbs test
    Sample percentile test
    Five number test
    Walsh test
Data Transposition
    Data centralisition
    Data normalization
    Data standarzation
    Data logarithmn transposition
    Data square transposition
    Data symmetrization
Descriptive Statistics
    Measures of central tendency: mean, median, harmonic mean, geometric mean, trimmed mean, square mean
    Measures of scale: variance, standard deviation, range, standard error, coefficient of variation, average absolute deviation, interquartile range
    Moments: skewness, kurtosis
Frequency Analysis
Hypothesis Test
    Compare Means
        One sample z test
        Two samples z test
        One sample t test
        Independent samples t test
        Paired samples t test
    Ratio Test
        One sample ratio test
        Two samples ratio test
    Compare Variances
        One sample variance test
        Two samples variance test(F test)
        K samples variance test(Levene test)
        K samples variance test(Bartlett test)
    Correlation Test
    Jarque-bera Test
Analysis of variance (ANOVA)
    One-way ANOVA
    Two-way ANOVA
    Two-way ANOVA with repeated measures
Non-parametric Test
    Binomial test
    One sample Chi-square test
    Two samples Chi-square test
    One sample Kolmogorov-Smirnov test
    Two samples Kolmogorov-Smirnov test
    One sample sign test
    Runs test
    Wilcoxon signed rank test
    Mann Whitney U test
    Shapiro Wilk test
    Anderson Darling test
    Lilliefors test
    D'Agostino test
    Mcnemar test
    Kruskal Wallis test
    Friedman test
    Cochran Q test
    Kendall's W test
Regression Analysis
    Univariate linear regression
    Multivariate linear regression
    Trend surface analysis
    Stepwise regression
Correlation Analysis
    Bivariate correlation analysis
    Partial correlation analysis
Cluster Analysis
    Stepwise cluster analysis
    Hierarchial cluster analysis
Discriminant Analysis
    Stepwise discriminant analysis
Principal Component Analysis
Factor Analysis
Correspondence Analysis

Data Fitting

Curve Fitting
Nonlinear curve fitting
Surface fitting
Volume data fitting
Polynomial fitting
Levenberg-Marquardt method

Interpolation

Univariate lagrange interpolation
Univariate three points interpolation
Univariate continued fraction interpolation
IDW interpolation

Integration

Variable step size trapezoidal integration
Adaptive trapezoidal integration
Variable step size Simpson method
Romberg method
Continued fraction method
Legendre Gauss quadrature method

Linear Equations

Gaussian elimination method
Gaussian-Yordan method

Nonlinear Equation(s)

Secant method
Bisect method
Method of false position
Newton iteration method
Continued fraction method
Qr root method
Quasi-Newton method to find real roots of nonlinear equations

Matrix Operations

Basic arithmetic operations(Addition, subtraction, multiply a constant, multiplization)
Transpose
Inversion
Determinant
Rank
LU decomposition
QR decomposition
Singular value decomposition
Generalized inversion
Eigenvalues and eigenvectors

Optimisation

Golden root method to find real root of nonlinear equation
Simplex method of linear programming
Gradient method for solving multivariate nonlinear equation
Simplex method for solving multivariate nonlinear equation

Complex Number Operations

 
     
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