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Keywords:
regression model; nonlinear hypothesis; linearization
regression model; nonlinear hypothesis; linearization
Summary:
In weakly nonlinear regression model a weakly nonlinear hypothesis can be tested by linear methods if an information on actual values of model parameters is at our disposal and some condition is satisfied. In other words we must know that unknown parameters are with sufficiently high probability in so called linearization region. The aim of the paper is to determine this region.
References:
[1] Kubáček L., Kubáčková L.: Regression models with a weak nonlinearity. Technical report Nr. 1998.1, Universität Stuttgart, 1998, 1–67.
[2] Kubáček L., Kubáčková L.: Statistics, Metrology. : Vyd. Univ. Palackého, Olomouc. 2000 (in Czech).
[3] Kubáček L., Kubáčková L.: Statistical problems of a determination of isobestic points. Folia Fac. Sci. Nat. Univ. Masarykianae Brunensis, Math. 11 (2002), 139–150. MR 1994204 | Zbl 1046.62067
[4] Rao C. R.: Linear Statistical Inference, its Application. : J. Wiley, New York–London–Sydney. 1965. MR 0221616
[5] Tesaříková E., Kubáček L.: A test in nonlinear regression models. Demoprogram. Department of Algebra and Geometry, Faculta of Science, Palacký University, Olomouc, 2004 (in Czech).
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