diff --git a/src/R/challenger_R_org_Windows_64bits.org b/src/R/challenger_R_org_Windows_64bits.org index 9984ed76d7ee619a59738baf046e85a8cd18e3d6..60f3057abea78297ef83f0b815c0b31acced9eb0 100644 --- a/src/R/challenger_R_org_Windows_64bits.org +++ b/src/R/challenger_R_org_Windows_64bits.org @@ -170,9 +170,6 @@ Let's visually inspect how temperature affects malfunction: plot(data=data, Malfunction/Count ~ Temperature, ylim = c(0,1)) #+end_src -#+RESULTS: -[[file:c:/Users/dondon/AppData/Local/Temp/babel-mb830V/figuremlknwM.png]] - * Logistic regression Let's assume O-rings independently fail with the same probability @@ -232,9 +229,6 @@ plot(tempv,rmv,type="l",ylim=c(0,1)) points(data=data, Malfunction/Count ~ Temperature) #+end_src -#+RESULTS: -[[file:c:/Users/dondon/AppData/Local/Temp/babel-mb830V/figurePDN133.png]] - This figure is very similar to the Figure 4 of Dalal /et al./ *I have managed to replicate the Figure 4 of the Dalal /et al./ article.* @@ -249,9 +243,6 @@ ggplot(data, aes(y=Malfunction/Count, x=Temperature)) + xlim(30,90) + ylim(0,1) + theme_bw() #+end_src -#+RESULTS: -[[file:c:/Users/dondon/AppData/Local/Temp/babel-mb830V/figureUmDY5S.png]] - I don't get any warning from ~ggplot2~ indicating /"non-integer #successes in a binomial glm!"/ but this confidence region seems huge... It seems strange to me that the uncertainty grows so large for @@ -335,9 +326,6 @@ ggplot(data=data_flat, aes(y=Malfunction, x=Temperature)) + geom_point(alpha=.5, size=.5) + xlim(30,90) + ylim(0,1) + theme_bw() #+end_src -#+RESULTS: -[[file:c:/Users/dondon/AppData/Local/Temp/babel-mb830V/figureEStjqI.png]] - This confidence interval seems much more reasonable (in accordance with the data) than the previous one. Let's check whether it corresponds to the prediction obtained when calling directly @@ -375,7 +363,15 @@ pred_link #+end_src #+RESULTS: -: Erreur : objet 'pred.link' introuvable +: $fit +: 1 +: 1.616942 +: +: $se.fit +: [1] 1.659473 +: +: $residual.scale +: [1] 1 #+begin_src R :results output :session *R* :exports both logistic_reg$family$linkinv(pred_link$fit)