changes and thanks .md

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-0.11.2.0
-========
-
-- geigSH' (symmetric generalized eigensystem)
-
-- mapVectorWithIndex
-
-
-0.11.1.0
-========
-
-- exported Mul
-
-- mapMatrixWithIndex{,M,M_}
-
-0.11.0.0
-========
-
-- flag -fvector default = True
-
-- invlndet (inverse and log of determinant)
-
-- step, cond
-
-- find
-
-- assoc, accum
-
-0.10.0.0
-========
-
-- Module reorganization
-
-- Support for Float and Complex Float elements (excluding LAPACK computations)
-
-- Binary instances for Vector and Matrix
-
-- optimiseMult
-
-- mapVectorM, mapVectorWithIndexM, unzipVectorWith, and related functions.
-
-- diagRect admits diagonal vectors of any length without producing an error,
-  and takes an additional argument for the off-diagonal elements.
-
-- different signatures in some functions
-
-0.9.3.0
-=======
-
-- flag -fvector to optionally use Data.Vector.Storable.Vector
-  without any conversion.
-
-- Simpler module structure.
-
-- toBlocks, toBlocksEvery
-
-- cholSolve, mbCholSH
-
-- GSL Nonlinear Least-Squares fitting using Levenberg-Marquardt.
-
-- GSL special functions moved to separate package hmatrix-special.
-
-- Added offset of Vector, allowing fast, noncopy subVector (slice).
-  Vector is now identical to Roman Leshchinskiy's Data.Vector.Storable.Vector,
-  so we can convert from/to them in O(1).
-
-- Removed Data.Packed.Convert, see examples/vector.hs
-
-0.8.3.0
-=======
-
-- odeSolve
-
-- Matrix arithmetic automatically replicates matrix with single row/column
-
-- latexFormat, dispcf
-
-0.8.2.0
-=======
-
-- fromRows/fromColumns now automatically expand vectors of dim 1
-  to match the common dimension.
-  fromBlocks also replicates single row/column matrices.
-  Previously all dimensions had to be exactly the same.
-
-- display utilities: dispf, disps, vecdisp
-
-- scalar
-
-- minimizeV, minimizeVD, using Vector instead of lists.
-
-0.8.1.0
-=======
-
-- runBenchmarks
-
-0.8.0.0
-=======
-
-- singularValues, fullSVD, thinSVD, compactSVD, leftSV, rightSV
-  and complete interface to [d|z]gesdd.
-  Algorithms based on the SVD of large matrices can now be
-  significantly faster.
-
-- eigenvalues, eigenvaluesSH
-
-- linearSolveLS, rq
-
-0.7.2.0
-=======
-
-- ranksv
-
-0.7.1.0
-=======
-
-- buildVector/buildMatrix
-
-- removed NFData instances
-
-0.6.0.0
-=======
-
-- added randomVector, gaussianSample, uniformSample, meanCov
-
-- added rankSVD, nullspaceSVD
-
-- rank, nullspacePrec, and economy svd defined in terms of ranksvd.
-
-- economy svd now admits zero rank matrices and return a "degenerate
-  rank 1" decomposition with zero singular value.
-
-- added NFData instances for Matrix and Vector.
-
-- liftVector, liftVector2 replaced by mapVector, zipVector.
-