search for: fur3

...lt;- rep(0, each=2) for (i in seq(1:2)) { n <- dim(daten)[1] ix <- sample(n,200) # producing samples samp_i <- daten[ix,] stichproben[i] <- samp_i # doesn???t works # Calculation of the model: posterior_i <- MCMClogit(y ~ fbl.ind + fekq3 + febitda4 + fuvs + fkru + fzd + fur3, data=samp_i, b0=prior, B0=precision, tune=0.5) # calculation ergebnisse[i] <- summary(posterior_i) # saving the results (works) } --snip-- I have a data set called "daten". I produce samples of the size 200. The samples are saved in samp_i. Question: How is the easiest way to sav...

...amp_i <- daten[ix,] # draw samples y <- sum(samp_i$y) # number of defaults stichproben200[[i]] <- samp_i # saving the samples default200[i] <- y # saving the number of defaults # Modell berechnen: posterior_i <- MCMClogit(y ~ fbl.ind + fekq3 + febitda4 + fuvs + fkru + fzd + fur3, data=samp_i, b0=prior, B0=precision, tune=0.5) # calculation ergebnisse200[i] <- summary(posterior_i) # saving the results } # write out the solutions into an excel-file write.csv2(ergebnisse200, "ergebnisse.csv") --snip-- My solution has the following form: http://img296.imagesha...