EasyFit 5.0
Fit more than 55 probability distributions to your data, select the best model, and apply the results to make business decisions. Reduce your analysis & simulation times by using EasyFit as a stand-alone application or with Microsoft Excel.
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3.60 MB · easyfit-setup.exe
1.8Kdownloads
4this week
$499Commercial
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About EasyFit
EasyFit allows to easily and quickly select the probability distribution which best fits to data, reducing your analysis times by 70-95% over manual methods. It includes numerous features designed to save you time, prevent analysis errors, and help you make better business decisions.
The key feature of EasyFit is the ability to automatically fit over 55 distributions to sample data and select the best model (advanced users can apply the manual fitting feature). The goodness of fit tests (Kolmogorov-Smirnov, Anderson-Darling, Chi-Squared) and a variety of graphs (probability density, cumulative probability, survival, hazard, P-P plot, Q-Q plot etc.) help you compare the fitted distributions and ensure you have selected the most valid model.
Finally, you can apply the integrated StatAssist tool to make business decisions based on the analysis results.
The advanced Excel integration enables you to use the power of EasyFit right in Excel. EasyFit allows to perform worksheet data analysis and simulation, create advanced worksheet models, and develop VBA applications dealing with uncertainty to tailor your specific needs.
Supported Distributions: Bernoulli, Beta, Binomial, Burr (Singh-Maddala), Cauchy (Lorentz), Chi-Squared, Dagum (Inverse Burr), Erlang, Error (Exponential Power), Error Function, Exponential, F Distribution, Fatigue Life (Birnbaum-Saunders), Frechet, Gamma, Generalized Gamma, Generalized Extreme Value (GEV), Generalized Logistic, Generalized Pareto, Geometric, Gumbel (Extreme Value), Hyperbolic Secant, Hypergeometric, Inverse Gaussian, Johnson SB, Johnson SU, Kumaraswamy, Laplace (Double Exponential), Levy, Logarithmic, Logistic, Lognormal, Log-Gamma, Log-Pearson III (LP3), Nakagami, Negative Binomial, Normal, Pareto, Pareto 2 (Lomax), Pearson 5 (Inverse Gamma), Pearson 6, Pert, Poisson, Power Function, Rayleigh, Reciprocal, Rice (Nakagami-n), Student's t, Triangular, Uniform, Wakeby, Weibull.
The key feature of EasyFit is the ability to automatically fit over 55 distributions to sample data and select the best model (advanced users can apply the manual fitting feature). The goodness of fit tests (Kolmogorov-Smirnov, Anderson-Darling, Chi-Squared) and a variety of graphs (probability density, cumulative probability, survival, hazard, P-P plot, Q-Q plot etc.) help you compare the fitted distributions and ensure you have selected the most valid model.
Finally, you can apply the integrated StatAssist tool to make business decisions based on the analysis results.
The advanced Excel integration enables you to use the power of EasyFit right in Excel. EasyFit allows to perform worksheet data analysis and simulation, create advanced worksheet models, and develop VBA applications dealing with uncertainty to tailor your specific needs.
Supported Distributions: Bernoulli, Beta, Binomial, Burr (Singh-Maddala), Cauchy (Lorentz), Chi-Squared, Dagum (Inverse Burr), Erlang, Error (Exponential Power), Error Function, Exponential, F Distribution, Fatigue Life (Birnbaum-Saunders), Frechet, Gamma, Generalized Gamma, Generalized Extreme Value (GEV), Generalized Logistic, Generalized Pareto, Geometric, Gumbel (Extreme Value), Hyperbolic Secant, Hypergeometric, Inverse Gaussian, Johnson SB, Johnson SU, Kumaraswamy, Laplace (Double Exponential), Levy, Logarithmic, Logistic, Lognormal, Log-Gamma, Log-Pearson III (LP3), Nakagami, Negative Binomial, Normal, Pareto, Pareto 2 (Lomax), Pearson 5 (Inverse Gamma), Pearson 6, Pert, Poisson, Power Function, Rayleigh, Reciprocal, Rice (Nakagami-n), Student's t, Triangular, Uniform, Wakeby, Weibull.
| Requirements | 128 MB RAM |
|---|---|
| Release info | Major Update on Oct 23, 2008 |
| Release notes | 15 new distributions, new Excel worksheet & VBA functions. |
| Related tags | distribution fitting probability fit goodness |
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