Forecasting principles and practice

Forecasting principles and practice - Forecasting...

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Forecasting: principles and practice time series analysis and its applications: with R examples robert shumway and david stoffer have R and R studio installed --------------------- inclass.R y<- means that y is assigned to something y<-4 y assigned to 4 rm(x,y) get rid of x and y from your memory z<-c(5,9,1,0) a vector with those values c → concatenate 2 things together as long as they are of the same dimension length(z) vector of length 4 sequences are equally spaced seq(8,20,length=6) equally spaced 6 values from 8-20 rep() → repeat to reference to the 2nd element in x → x[2] negative sign in front of it means that you don’t want it
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Unformatted text preview: cbind(x,y) → bind them column wise rbind(x,y) → bind them row wise rbind(z,z) go over this nr means nrow means how many rows to make it go over z<-matrix(c….),nr=2,byrow=T) y%*%x matrix multiplication y*z element multiplication t(z) transpose matrix z solve(x) compute the inverse of x attach(trees) now i’m working with the tree object. ..look at the variables in trees apply(trees,2,mean) apply mean to the tree object by column [ 1 is row, 2 is column] as.characters the function reads the input as characters one by one rnorm(how many, mean, standard deviation...
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  • Fall '13
  • Lin
  • Time series analysis, David Stoffer, robert shumway, y*z element multiplication

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