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- W2030804129 abstract "Abstract A method and FORTRAN program is presented for calculating a multivariate functional regression, analogous to the reduced major axis regression for the bivariate situation. The method is based on rotating the coordinates of the experimental points with respect to the axes. The rotation is such that the direction of distances whose sums of squares are to be minimized now are parallel to the “ Y ” axis. A classical regression, using matrix expressions, then is performed following which the best-fit line is rotated back to give its equation in the original space. The rotation is performed to give a regression in a direction proportional to the square roots of the total variances of the parameters in the regression (which is the reduced major axis regression for the bivariate situation). Standard errors of the regression coefficients are estimated by a Monte-Carlo method. The program also can perform a classical regression, simply be omitting the rotation phase. The two examples used in Part 1 are repeated. In both examples the program gives the same result for classical regression as other methods including the function minimization method of Part 1. The first example is a bivariate example and the program gives the same answer as analytical expressions for the reduced major axis regression. In the second, the multivariate example, the program gives the same result as the function minimization method of Part 1." @default.
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- W2030804129 date "1991-01-01" @default.
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- W2030804129 title "Multiple functional regression—II. Rotation followed by classical regression technique" @default.
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- W2030804129 doi "https://doi.org/10.1016/0098-3004(91)90089-v" @default.
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