# Asymptotic confidence intervals

## Asymptotic confidence intervals for NLS regression in R

Introduction Nonlinear regression model As a model setup, we consider noisy observations $$y_1,\ldots, y_n \in \mathbb{R}$$ obtained from a standard nonlinear regression model of the form: \begin{aligned} y_i &\ = \ f(\boldsymbol{x}_i, \boldsymbol{\theta}) + \epsilon_i, \quad i = 1,\ldots, n \end{aligned} where $$f: \mathbb{R}^k \times \mathbb{R}^p \to \mathbb{R}$$ is a known nonlinear function of the independent variables $$\boldsymbol{x}_1,\ldots,\boldsymbol{x}_n \in \mathbb{R}^k$$ and the unknown parameter vector $$\boldsymbol{\theta} \in \mathbb{R}^p$$ that we aim to estimate.