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A height-diameter model has the following structure \[\begin{equation}
h_i=f({\theta},d_i) + \epsilon_i, \label{eq:modh.0}
\end{equation}\]
where: \(h_i\) is height at the \(i\)-th tree; \(d_i\) is diameter at breast height at the \(i\)-th tree; \(f()\) is a mathematical function; \({\theta}\) is a vector of coefficients (i.e., parameters) of model \(f()\); \(\epsilon_{i}\) is the random term for the \(i\)-th tree following a Gaussian probability density function having an expected value of zero and variance \(\sigma^2_{\epsilon}\). Noice that function \(f()\) could either be linear o non-linear.