000			01806nab a22003137a 4500
001			G69454
003			MX-TxCIM
005			20230731172154.0
008			121211b |||p||p||||||| |z||| |
022			_a0006-341X
022			_a1541-0420
024			_2https://doi.org/10.2307/2528220
040			_aMX-TxCIM
041			_aeng
090			_aREP-1449
100	1		_aNelder, J.A. _931382
245	1	0	_aInverse polynomials, a useful group of multi-factor response functions
260			_c1966 _aUnited Kingdom : _bInternational Biometric Society,
340			_aPrinted
520			_aIf x1, x2,..., xk represent the levels of k experimental factors and y is the mean response, then the inverse polynomial response function is defined by x1x 2 ⋯ xk/y = Polynomial in (x1, x2 ⋯, xk). Arguments are given for preferring these surfaces to ordinary polynomials in the description of certain kinds of biological data. The fitting of inverse polynomials under certain assumptions is described, and shown to involve no more labour than that of fitting ordinary polynomials. Complications caused by the necessity of fitting unknown origins to the xi are described and the estimation process illustrated by an example. The goodness of fit of ordinary and inverse polynomials to four sets of data is compared and the inverse kind shown to have some advantages. The general question of the value of fitted surfaces to experimental data is discussed.
546			_aText in English
595			_aRPC
650		7	_2AGROVOC _931377 _aMathematical analysis
650		7	_2AGROVOC _930608 _aBiological data
650		7	_2AGROVOC _91313 _aYields
650		7	_2AGROVOC _94859 _aModels
773	0		_tBiometrics _gv. 22, no. 1, p. 128-141 _dUnited Kingdom : International Biometric Society, 1966. _x0006-341X
942			_cJA _2ddc
999			_c20073 _d20073