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| R2011b Documentation → Statistics Toolbox | |
Learn more about Statistics Toolbox |
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| Contents | Index |
This table summarizes what's new in Version 7.4 (R2010b):
| New Features and Changes | Version Compatibility Considerations | Fixed Bugs and Known Problems |
|---|---|---|
Yes | Yes | Bug
Reports |
New features and changes introduced in this version are:
Compute Partial Correlation of Two Variables Correcting for All Other Variables
Control Location and Orientation of Marginal Histograms with scatterhist
Statistics Toolbox now supports parallel execution for the following functions:
For more information, see the Parallel Statistics chapter in the User's Guide.
New filter algorithm, relieff, is based on nearest neighbors. The ReliefF algorithm accounts for correlations among predictors by computing the effect of every predictor on the class label (or true response for regression) locally and then integrates these local estimates over the entire predictor space.
nlmefit now supports the following error models:
combined
constant
exponential
proportional
You can specify an error model with both nlmefitsa and nlmefit.
The nlmefit bic calculation has changed. Now the degrees of freedom value is based on the number of groups rather than the number of observations. This conforms with the bic definition used by the nlmefitsa function.
Both nlmefit and nlmefitsa now store the estimated error parameters in the errorparm field of the output stats structure. The rmse field of the structure now contains the root mean squared residual for all error models; this value is computed on the log scale for the exponential model.
In the previous release, the rmse field was used by nlmefitsa for both mean squared residual and the estimated error parameter. Change your code, if necessary, to address the appropriate field in the stats structure.
As described in nlmefit Support for Error Models, and nlmefitsa changes, nlmefit now calculates different bic values than in previous releases.
The new surrogate splits feature in classregtree allows for better handling of missing values, more accurate estimation of variable importance, and calculation of the predictive measure of association between variables.
TreeBagger and CompactTreeBagger classes have two new properties:
NVarSplit provides the number of decision splits for each predictor variable.
VarAssoc provides a measure of association between pairs of predictor variables.
The linkage function has improved performance for the centroid, median, and single linkage methods.
The linkage and pdist hierarchical cluster analysis functions support larger array dimensions with 64-bit platforms, so can handle larger problems.
The distribution fitting GUI (dfittool) now allows you to export fits to the MATLAB workspace as probability distribution fit objects. For more information, see Modeling Data Using the Distribution Fitting Tool.
If you load a distribution fitting session that was created with previous versions of Statistics Toolbox, you cannot save an existing fit. Fit the distribution again to enable saving.
partialcorr now accepts a new syntax, RHO = partialcorr(X), which returns the sample linear partial correlation coefficients between pairs of variables in X, controlling for the remaining variables in X. For more information, see the function reference page.
quantile now accepts a new syntax, Y = quantile(X,N,...), which returns quantiles at the cumulative probabilities (1:N)/(N+1) where N is a scalar positive integer value.
scatterhist now accepts three parameter name/value pairs that control where and how the histogram plots appear. The new parameter names are NBins, Location, and Direction. For more information, see the function reference page.
bootci has a new output option which returns the bootstrapped statistic computed for each of the NBoot bootstrap replicate samples. For more information, see the function reference page.
 | Version 7.5 (R2011a) Statistics Toolbox Software | Version 7.3 (R2010a) Statistics Toolbox Software |  |
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