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Contact
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To deal with a large number of responses, the
NemrodW
software offers to investigate the connections between the responses using the principal components analysis.
The statistical design of experiments software constructs computer-generated designs to deal with particular situations where the standard designs cannot be used. The software estimates several "a priori" criteria to help the experimenters to choose the experimental design. The software gives a lot of diagnostic "a posteriori" criteria to judge of the goodness of fit. All the statistics and the graphics can be saved in a report that can be modified in any word-processing package.
Principal Components Analysis |
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- Eigenvalues, eigenvectors. |
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- Squared-cosine and contributon of each observation. |
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- Correlation circle. |
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- Bi-plot eigenvectors and variables. |
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- Bi-plot eigenvectors and observations. |
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Miscellaneous |
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Computer- generated design |
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- To repair broken experimental designs. |
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- To augment an experimental design. |
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- To statisfy experimental constraints (cost, between factors, run number...). |
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- To fit a particular model. |
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- User-defined candidate sets (weighted or not). |
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Experimental design criteria |
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- Model terms: VIF, information, dispersion, alias and correlation matrix, determinants, G-efficacity... |
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- Prediction: maximale variance function, scale predicted variance contour plot and 3D surface, Khuri... |
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Analysis |
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- Least squared and ridge regressions. |
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- Response Box plot, Box-Cox method for selecting a transformation, external variance estimate... |
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- ANOVA, estimate standard error and t-test. |
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- Résiduals, R-student, studendized residuals, standardized residuals, Cook's distance... |
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- Plot and Normal plot of residuals, standardized residuals and R-student residuals. |
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Tips |
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- Report file (RTF format) including plots and tables.
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- Editable design. |
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- Tutorials. |
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- Context sensitive help. |
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To buy the DOE software or to get a free evaluation version, please fill out the information request.
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