Statistics ANOVA Experimental design Miscellaneous: Difference between revisions

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:[[anova2w]] - Two-way analysis of variance.
:[[anova2w]] - Two-way analysis of variance.
:[[anovadoe]] - Function to perform ANOVA for 2^k factorial model X, Y data.
:[[anovadoe]] - Function to perform ANOVA for 2^k factorial model X, Y data.
:[[boxbehnken]] - Create a Box-Behnken Design of Experiments.
:[[boxbehnken]] - Create a Box-Behnken Design of Experiments.
:[[ccdface]] - Create a Face-Centered Central Composite Design of Experiments.
:[[ccdface]] - Create a Face-Centered Central Composite Design of Experiments.

Revision as of 15:43, 12 September 2011

anova1w - One-way analysis of variance.
anova2w - Two-way analysis of variance.
anovadoe - Function to perform ANOVA for 2^k factorial model X, Y data.
boxbehnken - Create a Box-Behnken Design of Experiments.
ccdface - Create a Face-Centered Central Composite Design of Experiments.
ccdsphere - Create a Spherical Central Composite Design of Experiments.
corrmap - Correlation map with variable grouping.
cov_cv - Estimation of a regularized inverse covariance matrix.
distslct - Selects samples on outside of data space.
doeeffectsplot - Create main effect or interaction plot, incl LSD bars.
doegen - Generate a Design of Experiments (DOE) DataSet object.
doegui - Design of Experiments tool.
doeinteractions - Calculates interaction terms of a raw DOE matrix.
doerunsheet - Create a doe run sheet.
doescale - Convert coded DOE to scaled DOE or scaled back to coded.
doptimal - Selects samples based on D-Optimal criteria.
durbin_watson - Criterion for measure of continuity.
exteriorpts - Selects samples on outside of data space after normalizing data.
factdes - Full factorial design of experiments.
ffacconfusion - Generates confusion table for a fractional factorial DOE.
ffacdes1 - Fractional factorial design of experiments.
ftest - F test and inverse F test statistic.
percentile - Finds percentile point (similar to MEDIAN).
reducennsamples - Selects a subset of samples by removing nearest neighbors.
stdsslct - Selects data subsets (often for use in standardization).
ttestp - Evaluates t-distribution and its inverse.

(Sub topic of Categorical_Index)