Respuesta :

jepessoa

Answer:

b. other than 1

Explanation:

Nonlinear models are called that way because they are not linear in parameters. In order for this nonlinear characteristic to exist, the exponents of the parameters must be any number other than 1.

While linear models can have a nonlinear relationship between the predictors and independent variables. But when you analyze the mean (predictor), it must be linear with the parameters.

gauravsingh23VT

The nonlinear models have an exponent other than 1. As the nonlinear exponent estimating a regression model, convert the forecast variable y and/or the predictor variable x.

What is the nonlinear model?

Non-linearity is a term used in statistics to describe a situation where there is no direct relationship between the two variables that are independent and independent. The input is not directly affected by the change in the relationship in the output in the direct proposition.

Thus, option B is correct.

For further details about the non-linear model refer to this link:

https://brainly.in/question/1327517

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