Least Squares

dc.contributor	Universidade Estadual Paulista (UNESP)
dc.creator	Maes, Chris
dc.date	2016-10-26T17:48:08Z
dc.date	2016-10-26T17:48:08Z
dc.date.accessioned	2017-04-06T11:38:27Z
dc.date.available	2017-04-06T11:38:27Z
dc.identifier	http://acervodigital.unesp.br/handle/unesp/360888
dc.identifier	http://objetoseducacionais2.mec.gov.br/handle/mec/5347
dc.identifier.uri	http://repositorioslatinoamericanos.uchile.cl/handle/2250/957170
dc.description	When a matrix A is square with full rank, there is a vector x that satisfies the equation Ax=b for any b. However, when A is not square or does not have full rank, such an x may not exist, because b does not lie in the range of A. In this case, called the least squares problem, we seek the vector x that minimizes the length (or norm) of the residual vector r=Ax-b. The four vectors Ax, b, r, and rmin are color coded and the plane is the range of the matrix A. The plane shown is the set of all possible vectors Ax
dc.description	Componente Curricular::Educação Superior::Ciências Exatas e da Terra::Matemática
dc.publisher	Wolfram
dc.relation	LeastSquares.nbp
dc.rights	Demonstration freeware using Mathematica Player
dc.subject	Approximation Methods
dc.subject	Educação Superior::Ciências Exatas e da Terra::Matemática::Análise Complexa
dc.title	Least Squares
dc.type	Otro