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[. . . ] Statistics ToolboxTM Release Notes
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The software described in this document is furnished under a license agreement. The software may be used or copied only under the terms of the license agreement. [. . . ] The qrandstream function provides corresponding quasi-random number streams for intermittent sampling.
Regression Analysis
The new plsregress function performs partial least-squares regression for data with correlated predictors.
Statistical Visualization
The normspec function now shades regions of a normal density curve that are either inside or outside specification limits.
Utility Functions
The statistics options structure created by statset now includes fields for TolTypeFun and TolTypeX, to specify tolerances on objective functions and parameter values, respectively.
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Version 6. 1 (R2007b) Statistics ToolboxTM Software
Version 6. 1 (R2007b) Statistics Toolbox Software
This table summarizes what's new in Version 6. 1 (R2007b): New Features and Changes Yes Details below Version Compatibility Considerations Yes Summary Fixed Bugs and Known Problems Bug Reports Includes fixes Related Documentation at Web Site No
New features and changes introduced in this version are organized by these topics: · "Cluster Analysis" on page 17 · "Design of Experiments" on page 18 · "Hypothesis Tests" on page 18 · "Probability Distributions" on page 18 · "Regression Analysis" on page 19 · "Statistical Visualization" on page 20
Cluster Analysis
The new gmdistribution class represents Gaussian mixture distributions, where random points come from different multivariate normal distributions with certain probabilities. The gmdistribution constructor creates mixture models with specified means, covariances, and mixture proportions, or by fitting a mixture model with a specified number of components to data. Methods for the class include: · fit -- Distribution fitting function · pdf -- Probability density function · cdf -- Cumulative distribution function · random -- Random number generator · cluster -- Data clustering
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Statistics ToolboxTM Release Notes
· posterior -- Cluster posterior probabilities · mahal -- Mahalanobis distance The cluster function for hierarchical clustering now accepts a vector of cutoff values, and returns a matrix of cluster assignments, with one column per cutoff value.
Compatibility Considerations
The kmeans function now returns a vector of cluster indices of length n, where n is the number of rows in the input data matrix X, even when X contains NaN values. In the past, rows of X with NaN values were ignored, and the vector of cluster indices was correspondingly reduced in size. Now the vector of cluster indices contains NaN values where rows have been ignored, consistent with other toolbox functions.
Design of Experiments
A new option in the D-optimal design function candexch specifies fixed design points in the row-exchange algorithm. A similar feature is already available for the daugment function, which uses the coordinate-exchange algorithm.
Hypothesis Tests
The kstest function now uses a more accurate method to calculate the p-value for a single-sample Kolmogorov-Smirnov test.
Compatibility Considerations
kstest now compares the computed p-value to the desired cutoff, rather than
comparing the test statistic to a table of values. Results may differ from those in previous releases, especially for small samples in two-sided tests where an asymptotic formula was used in the past.
Probability Distributions
A new fitting function, copulafit, has been added to the family of functions that describe dependencies among variables using copulas. The function fits parametric copulas to data, providing a link between models of marginal distributions and models of data correlations.
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Version 6. 1 (R2007b) Statistics ToolboxTM Software
A number of probability functions now have improved accuracy, especially for extreme parameter values. The functions are: · betainv -- More accurate for probabilities in P near 1. · binocdf -- More efficient and less likely to run out of memory for large values in X. · binopdf -- More accurate when the probabilities in P are on the order of
eps.
· fcdf -- More accurate when the parameter ratios V2. /V1 are much less than the values in X. · ncx2cdf -- More accurate in some extreme cases that previously returned
0.
· poisscdf -- More efficient and less likely to run out of memory for large values in X. · tcdf -- More accurate when the squares of the values in X are much less than the parameters in V. · tinv -- More accurate when the probabilities in P are very close to 0. 5 and the outputs are very small in magnitude. Function-style syntax for paretotails objects has been removed.
Compatibility Considerations
The changes to the probability functions listed above may lead to different, but more accurate, outputs than in previous releases. In previous releases, syntax of the form obj(x) for a paretotails objects obj invoked the cdf method. To evaluate the cumulative distribution function, use the syntax cdf(obj, x).
Regression Analysis
The new corrcov function converts a covariance matrix to the corresponding correlation matrix. The mvregress function now supports an option to force the estimated covariance matrix to be diagonal.
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Statistics ToolboxTM Release Notes
Compatibility Considerations
In previous releases the mvregress function, when using the 'cwls' algorithm, estimated the covariance of coefficients COVB using the estimated, rather than the initial, covariance of the responses SIGMA. The initial SIGMA is now used, and COVB differs to a degree dependent on the difference between the initial and final estimates of SIGMA.
Statistical Visualization
The boxplot function has a new 'compact' plot style suitable for displaying large numbers of groups.
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Version 6. 0 (R2007a) Statistics ToolboxTM Software
Version 6. 0 (R2007a) Statistics Toolbox Software
This table summarizes what's new in Version 6. 0 (R2007a): New Features and Changes Yes Details below Version Compatibility Considerations Yes Summary Fixed Bugs and Known Problems Bug Reports Includes fixes Related Documentation at Web Site No
New features and changes introduced in this version are organized by these topics: · "Data Organization" on page 21 · "Hypothesis Testing" on page 22 · "Multivariate Statistics" on page 22 · "Probability Distributions" on page 22 · "Regression Analysis" on page 23 · "Statistical Visualization" on page 24 · "Other Improvements" on page 24
Data Organization
New categorical and dataset arrays are available for organizing and processing statistical data. · Categorical arrays facilitate the use of nominal and ordinal categorical data. · Dataset arrays provide a natural way to encapsulate heterogeneous statistical data and metadata, so that it can be accessed and manipulated using familiar methods analogous to those for numerical matrices. · Categorical and dataset arrays are supported by a variety of new functions for manipulating the encapsulated data. [. . . ] If the data sample for a test leads to a p-value outside the range of tabulated values, then both jbtest and lillietest now return, with a warning, either the smallest or largest tabulated value. In previous versions, jbtest returned an approximate p-value and lillietest returned NaN.
Multinomial Distribution
The multinomial distribution has been added to the list of almost 50 probability distributions supported by the toolbox. · mnpdf -- Multinomial probability density function
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Version 5. 3 (R2006b) Statistics ToolboxTM Software
· mnrnd -- Multinomial random number generator
Regression Analysis
Multinomial Regression
Support has been added for multinomial regression modeling of discrete multi-category response data, including multinomial logistic regression. The following new functions supplement the regression models in glmfit and glmval by providing for a wider range of response values: · mnrfit -- Fits a multinomial regression model to data · mnrval -- Computes predicted probabilities for the multinomial regression model
Multivariate Regression
The new mvregress function carries out multivariate regression on data with missing response values. [. . . ]