Does there exist an analytical solution to the log-likelihood minimisation for a Gaussian model with linear variance?

Question

I'm trying to model some data using the following distribution: \begin{align} r &\sim \mathcal{N}(\mu, \sigma^2) \nonumber\\ \mu &= m_0 + m_1 d \nonumber\\ \sigma^2 &= s_0+s_1 d\nonumber\\ p(r_1, r_2, \dots, r_N) &= \prod_{i=1}^N \frac{1}{\sqrt{2\pi\sigma^2_i}}e^{\frac{1}{-2\sigma^2_i}(r_i-\mu_i)^2} \nonumber\\ \mathcal{L} &= -\frac{1}{2}\log\big(p(r_1, r_2, \dots, r_N)\big)\nonumber\\ &= -\frac{1}{2}\sum_{i=1}^N\log\Big(\frac{1}{\sqrt{2\pi\sigma^2_i}}e^{\frac{1}{-2\sigma^2_i}(r_i-\mu_i)^2}\Big) \nonumber\\ &= \sum_{i=1}^N\Big[\log\big(2\pi\sigma^2_i\big) + \frac{(r_i-\mu_i)^2}{\sigma^2_i}\Big]\nonumber \end{align}

I was wondering if it is possible to maximise this likelihood analytically to obtain fits for $m_0, m_1, s_0, s_1$. I know that there exists a solution if $\sigma^2$ is constant (simple OLS) but what if it isn't? (I tried the first few steps below but am stuck on the last line)

\begin{align} \frac{\partial\mathcal{L}}{\partial s_0} &= \sum_{i=1}^N \frac{\partial}{\partial \sigma^2_i}\frac{\partial\sigma^2_i}{\partial s_0}\Big[\log\big(2\pi\sigma^2_i\big) + \frac{(r_i-\mu_i)^2}{\sigma^2_i}\Big]\nonumber\\ &=\sum_{i=1}^N\frac{1}{\sigma_i^2}-\frac{(r_i-\mu_i)^2}{\sigma_i^4}=0 \nonumber\\ \end{align}

Answer 1

This is an extended comment rather than an answer.

An explicit solution for $\hat{m_0}$ and $\hat{m_1}$ exists in terms of $s_0$ and $s_1$ but I'm doubtful that an explicit solution exists for all 4 parameters.

$$\hat{m_0}=\frac{\left(\sum _{i=1}^n \frac{d_i}{s_1 d_i+s_0}\right) \left(\sum _{i=1}^n \frac{d_i r_i}{s_1 d_i+s_0}-\sum _{i=1}^n \frac{r_i}{s_1d_i+s_0}\right)}{\left(\sum _{i=1}^n \frac{d_i}{s_1 d_i+s_0}\right){}^2-\left(\sum _{i=1}^n \frac{1}{s_1 d_i+\text{s0}}\right) \sum _{i=1}^n \frac{d_i^2}{s_1 d_i+s_0}}$$

$$\hat{m_1}=\frac{\left(\sum _{i=1}^n \frac{d_i}{s_1 d_i+s_0}\right) \sum _{i=1}^n \frac{r_i}{s_1 d_i+s_0}-\left(\sum _{i=1}^n \frac{1}{s_1 d_i+s_0}\right) \sum _{i=1}^n \frac{d_i r_i}{s_1 d_i+s_0}}{\left(\sum _{i=1}^n \frac{d_i}{s_1 d_i+s_0}\right){}^2-\left(\sum _{i=1}^n \frac{1}{s_1 d_i+s_0}\right) \sum _{i=1}^n \frac{d_i^2}{s_1 d_i+s_0}}$$