The nonlinear normal model
DOI:
https://doi.org/10.33448/rsd-v11i12.26071Keywords:
Normal non-linear regression; Estimation of parameters; Confidence intervals; Hypothesis tests; Nonlinear models.Abstract
When referring to data analysis, there is a range of models that fit the data, such as linear regression models and also non-linear regression models. In statistics, nonlinear regression is a form of regression analysis, in which initially a certain mathematical function is adjusted to the data, it is important to emphasize that this adjustment can be made qualitatively using a scatter diagram. The main objective of this article will be to approach the nonlinear normal regression technique, where some methods for estimating the parameters of the nonlinear normal model, the precision the estimators, confidence intervals, hypothesis tests, some asymptotic results and the estimation of variance. Finally, a set of data regarding European Rabbits will be analyzed to demonstrate the applicability of the non-linear model, in which initially we try to adjust the data set to the linear normal model where the adjustment is not successful and then the non-linear normal model is considered, which was the model that best fit the data.
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