David: Response=rbinom(50,1,0.2), and yhat=runif(50) are simulating the output of a say logistic model, where Response is actual 0-1 responses, and yhat is the predicted response variable. I usually resample the original data to get some noise out of the data. I find it valuable if I can resample from a large sample than the original. (I know this is viewed by some as unorthodox.)
Your point: I only need Response as a column vector. That said, what would you alter, please? Thanks for your time. Regards, Bruce ______________ Bruce Ratner PhD The Significant Statistician™ (516) 791-3544 Statistical Predictive Analytics -- www.DMSTAT1.com Machine-Learning Data Mining -- www.GenIQ.net > On Apr 21, 2017, at 3:43 PM, David L Carlson <dcarl...@tamu.edu> wrote: > > You have an issue at the top with > > Resp <- data.frame(Response=rbinom(50,1,0.2), yhat=runif(50)) > Resp <- Resp[order(Response$yhat,decreasing=TRUE),] > > Since Response$yhat has not been defined at this point. Presumably you want > > Resp <- Resp[order(Resp$yhat,decreasing=TRUE),] > > The main issue is that you have a variable Response that is located in a data > frame called ResponseX10. > > In creating cum_R you need > > cum_R <- with(ResponseX10, cumsum(Response)) > > then dec_mean > > dec_mean <- with(ResponseX10, aggregate(Response, by=list(decc), mean)) > > then dd > > dd <- with(ResponseX10, cbind(Response, dd_)) > > > You might consider if Response really needs to be inside a data frame that > consists of a single column (maybe you do if you need to keep track of the > row numbers). If you just worked with the vector Response, you would not have > to use with() or attach(). > > I'm not sure what the first few lines of your code are intended to do. You > choose random binomial values and uniform random values and then order the > first by the second. But rbinom() is selecting random values so what is the > purpose of randomizing random values? If the real data consist of a vector of > 1's and 0's and those need to be randomized, sample(data) will do it for you. > > Then those numbers are replicated 10 times. Why not just select 500 values > using rbinom() initially? > > > David C > > > -----Original Message----- > From: BR_email [mailto:b...@dmstat1.com] > Sent: Friday, April 21, 2017 1:22 PM > To: David L Carlson <dcarl...@tamu.edu>; r-help@r-project.org > Subject: Re: [R] Looking for a package to replace xtable > > David: > I tried somethings and got a little more working. > Now, I am struck at last line provided: "dec_mean <- > aggregate(Response ~ decc, dd, mean)" > Any help is appreciated. > Bruce > > ***** > Resp <- data.frame(Response=rbinom(50,1,0.2), yhat=runif(50)) > Resp <- Resp[order(Response$yhat,decreasing=TRUE),] > > ResponseX10 <- do.call(rbind, replicate(10, Resp, simplify=FALSE)) > str(ResponseX10) > > ResponseX10 <- ResponseX10[order(ResponseX10$yhat,decreasing=TRUE),] > > str(ResponseX10) > head(ResponseX10) > > ResponseX10[[2]] <- NULL > ResponseX10 <- data.frame(ResponseX10) > str(ResponseX10) > > cum_R <- cumsum(Response) > cum_R > > sam_size <- n ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
