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articles/Chapter06.html

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articles/Chapter06.md

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``` r
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par(mfrow=c(1,1))
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matplot(x=t(matrix(1:nf,ncol=3, nrow=nf)),y=pred.int.sc,col="blue",type = "l",pch=16,lty=1,ylim=c(5,35), xlim=c(0,nf+1), xlab="Scenarios", ylab="Prediction",xaxt="n")
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points(x = 1:nf, y = pred.int.sc[2,], pch=16,col="blue")
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matplot(x=t(matrix(1:nf,ncol=3, nrow=nf)),y=pred.int.sc,col="blue",type = "l",pch=16,lty=1,ylim=c(8,32), xlim=c(0.5,nf+0.5), xlab="Scenarios", ylab="Predicted Open Box Office",xaxt="n")
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points(x = 1:nf, y = pred.int.sc[2,], pch=19,col="blue",cex=1.2)
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points(x = 1:nf, y = pred.mean.sc, pch=16,col="red")
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matplot(x=t(matrix((1:nf)+0.2,ncol=3, nrow=nf)),y=pred.int.hs,col="blue",type = "l",pch=16,lty=1,add=TRUE)
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points(x = (1:nf)+0.2, y = pred.int.hs[2,], pch=16,col="blue")
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points(x = (1:nf)+0.2, y = pred.int.hs[2,], pch=19,col="blue",cex=1.2)
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points(x = (1:nf)+0.2, y = pred.mean.hs, pch=16,col="red")
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axis(1,at=1:nf,labels=c("A","B","C","D"))
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pkgdown.yml

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Chapter07: Chapter07.html
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Chapter08: Chapter08.html
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Chapter09: Chapter09.html
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last_built: 2025-12-17T15:07Z
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last_built: 2025-12-17T18:12Z
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urls:
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reference: https://gregorkastner.github.io/BayesianLearningCode/reference
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article: https://gregorkastner.github.io/BayesianLearningCode/articles

search.json

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