 Summary of important user-visible changes for statistics 2.1.0:
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 Backwards incompatible improvements:
 ====================================

 ** createns:
    with no 'NSMethod', builds a KDTreeSearcher for data with at most 10
    columns, not sparse, under the euclidean, cityblock, chebychev or
    minkowski distance, as MATLAB does, where it always built an
    ExhaustiveSearcher.

 ** mnrfit:
    the raw and Pearson residuals of ordinal and hierarchical models have K-1
    columns, as in MATLAB, where they had one per category; the 'display'
    option is removed, MATLAB having none.

 New functions and methods:
 ==========================

 ** fitmnr, MultinomialRegression:
    multinomial regression of nominal, ordinal and hierarchical responses
    from a matrix, a table or a formula, with predict, feval, random, coefCI,
    coefTest, testDeviance, plotResiduals, plotSlice and partial dependence,
    as in MATLAB.

 Bug fixes:
 ==========

 ** cmdscale:
    eigenvalues that are numerically zero no longer add columns of noise to
    Y; the cutoff follows the precision of D, as in MATLAB (#530).

 ** ExhaustiveSearcher, hnswSearcher, KDTreeSearcher:
    a 'P' without the minkowski distance, and a 'Scale' or 'Cov' without its
    distance, raise an error, as in MATLAB, where they were ignored.

 ** fitcknn, ClassificationKNN:
    'Exponent' takes any positive scalar, where one that was not an integer
    raised an error.

 ** knnsearch, rangesearch, createns, fitcknn, ExhaustiveSearcher,
    hnswSearcher, KDTreeSearcher:
    a Minkowski exponent of Inf gives the Chebychev distance on every search
    method, where it raised an error and a fitcknn model fitted with it
    failed in predict (#533).

 ** knnsearch, rangesearch:
    the kd-tree search lost a row whose NaN fell on a split, so knnsearch
    failed once K reached it, measured a row holding a NaN by its other
    coordinates under the Chebychev distance, and skipped rows tied at the
    worst distance when the query and a split were the same infinity;
    'IncludeTies' returned nothing when the K-th distance was NaN; a 'P'
    without the minkowski distance raises an error, where it was ignored.

 ** mnrfit:
    a character matrix response takes each row as one label (#529); a matrix
    response row holding NaN leaves its observation out, and one holding
    several 1s counts that many observations, as in MATLAB; an observation
    left out keeps a NaN row in the residuals; a single category gives an
    empty fit, as in MATLAB, where it raised an error.

 ** pdist, pdist2:
    a Minkowski exponent of Inf gives the Chebychev distance, where every
    distance was 1 (#532); the Chebychev distance is NaN for a pair where
    either row holds a NaN, as in MATLAB, and where a coordinate difference
    is Inf - Inf, as for every other metric (MATLAB passes over it).

 ** ridge:
    a predictor with no variation is taken as a constant term, where every
    coefficient was NaN (#531); fewer than two rows left after removing NaN
    raise an error.

 Improvements:
 =============

 ** mnrfit:
    string and categorical responses are accepted, and responses may be row
    vectors (#529); a matrix response holds counts, one column per category,
    with new options 'interactions', 'weights', 'iterationlimit' and
    'tolerance', as in MATLAB.
