lstsq(a, b)

Solves the equation :None:None:`a x = b` by computing a vector x that minimizes the Euclidean 2-norm :None:None:`|| b - a x ||^2`. The equation may be under-, well-, or over- determined (i.e., the number of linearly independent rows of a can be less than, equal to, or greater than its number of linearly independent columns). If a is square and of full rank, then x (but for round-off error) is the "exact" solution of the equation.

Parameters

a : (M, N) array_like

"Coefficient" matrix.

b : {(M,), (M, K)} array_like

Ordinate or "dependent variable" values. If b is two-dimensional, the least-squares solution is calculated for each of the K columns of b.

Returns

x : {(N,), (N, K)} Array

Least-squares solution. If b is two-dimensional, the solutions are in the K columns of x.

residuals : {(1,), (K,)} Array

Sums of residuals; squared Euclidean 2-norm for each column in b - a*x . If b is 1-dimensional, this is a (1,) shape array. Otherwise the shape is (K,).

rank : Array

Rank of matrix a.

s : (min(M, N),) Array

Singular values of a.

Return the least-squares solution to a linear matrix equation using QR decomposition.

Examples

See :

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File: /dask/array/linalg.py#1362
type: <class 'function'>
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