From 3499303002424756bf0bbb419d6de5b46e8e54ef Mon Sep 17 00:00:00 2001 From: Romeo Valentin Date: Wed, 22 May 2024 18:10:00 -0700 Subject: [PATCH] fixup! fixup! Add Readme v1. --- README.md | 2 +- .../distribution_graph/distribution_graph.pdf | Bin 15643 -> 15643 bytes .../distribution_graph/distribution_graph.png | Bin 67162 -> 67162 bytes 3 files changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index e9ee8d2..a13f351 100644 --- a/README.md +++ b/README.md @@ -51,7 +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. diff --git a/figs/distribution_graph/distribution_graph.pdf b/figs/distribution_graph/distribution_graph.pdf index 50cb93910f4d175e3ef1a706a5f5ed000165580b..2e566b03b512bbaf2372adfe8a6a6ab8ff213e3a 100644 GIT binary patch delta 100 zcmbPTHM?rVVGC9Z0}Dg5$tNu2Ags-=Ekc={-ApZ<44jAzVSl~IMw7RWB1uFuA(4FG708wvmb