fixup! Add Readme v1.

README.md

@@ -51,9 +51,7 @@ Therefore `predictdist(::MCMCEstimator, xs, ys, nsamples)` will create `nsamples
 
 ### LSQEstimator
 The `LSQEstimator` works by sampling noise $\varepsilon^{(k)}$ from the noise model and repeatedly solving a least-squares parameter estimation problem for modified measurements $y - \varepsilon^{(k)}$, i.e.
-$$
-\theta = \arg \min_\theta \sum_i ((y_i - \varepsilon_i^{(i)}) - f(x, \theta))^2 \cdot w_i
-$$
+$$ \theta = \arg \min_\theta \sum_i ((y_i - \varepsilon_i^{(i)}) - f(x, \theta))^2 \cdot w_i $$
 for uncorrelated noise, where the weights $w_i$ are chosen as the inverse variance.
 For correlated noise, the weight results from the whole covariance matrix.