rpolyreg

Linear, multivariant and polynominal regression.

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Usage 1

rpolyreg(xvector, yvector {, m}):

x

x data vector

y

y data vector: y[i] = f(x[i] {, x[i]^2, .., x[i]^m})

m

the regression (polynom) order; m>0 (default=1)

Result 1

Approximate the function y using polynominal regression. The result is the vector r with the m+1 coefficients of the regression polynom.

yREG[i] = r[0] + r[1]*x[i] {+ r[2]*x[i]^2 + .. + r[m]*x[i]^m}

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Usage 2

rpolyreg(xmatrix, yvector {, m}):

x

x data matrix, the regression order is the number of independent variables m=ncol(x)

y

y data vector: y[i] = f(x[i,*])

Result 2

Approximate the function y using multivariant linear regression. The result is the vector r with the m+1 regression coefficients.

yREG[i] = r[0] + r[1]*x[i,0] + .. + r[m]*x[i,m-1]

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See also

rpoly, interp, rleqs, cleqs, svd

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