From 11643a07077df3b7bd59b95ce28867b43287d493 Mon Sep 17 00:00:00 2001 From: Arnaud Legrand Date: Mon, 24 Sep 2018 10:52:41 +0200 Subject: [PATCH] Maths cleanups --- README.md | 11 ++++------- 1 file changed, 4 insertions(+), 7 deletions(-) diff --git a/README.md b/README.md index 2cc25b9..a7e5b7b 100644 --- a/README.md +++ b/README.md @@ -12,17 +12,14 @@ On the fourth page of this article, they indicate that the maximum likelihood estimates of the logistic regression using only temperature are: $`\hat{\alpha}=5.085`$ and $`\hat{\beta}=-0.1156`$ and their asymptotic standard errors are $`s_{\hat{\alpha}}=3.052`$ and -$s_{\hat{\beta}}=0.047`$. The Goodness of fit indicated for this model -was $`G^{2}=18.086`$ with 21 degrees of freedom. Our goal is to +$`s_{\hat{\beta}}=0.047`$. The Goodness of fit indicated for this model +was $`G^{2} = 18.086`$ with 21 degrees of freedom. Our goal is to reproduce the computation behind these values and the Figure 4 of this article, possibly in a nicer looking way. -
-**[Here is our successful replication of Dalal et al. results using -R](challenger.pdf)**. - -
+[*Here is our successful replication of Dalal et al. results using +R*](challenger.pdf). 1. Try to **replicate the computation** from Dalal et al. In case it helps, we provide you with two implementations of this case study -- 2.18.1