rpolyreg

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Linear, multivariant and polynominal regression.


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}

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 a 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]

See also
rpoly, interp

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