search for: case4

...g like #|$ case3.omitting the random effect for B from case1 case3<-update(case1,random=~1|C),so I just type 1,so the random effect of B will be removed from the model,there only left random effect of c ,the random effect I removed ,which include both random intercept and slope ,correct?? case4:omitting the random intercept case4<-update(case1,random=B-1|C) this code I got from some paper,it said by inputing B-1|C,then the random intercept is removed,so,if I want to remove random slode,I input B-2|C,it doesnt work out. case5 :how to know the both random effect of B,and C,I do...

...composed of seven-column as following: E1 E2 E3 E4 E5 E6 E7 Case1 -505.85 -75.32 494.52 -12.31 -98.96 50.34 -48.62 Case2 -50.46 -60.97 68.32 -8.66 -51.77 25.17 -26.60 Case3 -253.00 -54.99 243.48 -8.76 -73.27 35.46 -37.81 Case4 94.73 -20.27 -83.70 -3.17 -12.41 15.01 2.6 To adjust x-axis scale per column, I used prepanel function followed by scales argument. But then I wanted to mimic "alternating" option manually for x-axis location to prevent congestion among adjacent x-axis numbers. How can I...

...#39; must be numeric below an subset from my dataset: variable1 variable2 variable3 variable4 variable5 variable6 variable7 variable8 variable9 variable10 variable11 variable12 variable13 case1 0 0 0 0 0 1 0 0 1 1 0 0 0 case2 0 0 0 0 0 1 0 NA NA 1 0 0 0 case3 0 0 0 0 0 1 0 0 1 1 0 0 0 case4 1 0 0 0 0 1 0 1 0 1 0 0 0 case5 0 0 0 0 0 1 0 0 1 1 0 0 0 case6 0 1 0 0 0 1 0 1 0 1 0 0 0 case7 0 1 0 0 0 1 0 0 1 1 0 0 0 case8 0 0 0 0 0 1 0 1 0 1 0 0 0 case9 0 0 0 0 0 1 0 1 0 1 0 0 0 case10 0 0 0 0 0 1 0 0 1 1 0 0 0 case11 1 0 0 1 0 1 1 1 0 1 0 0 0 case12 0 0 0 1 1 0 1 1 0 1 0 0 0 ........

I have a function "eval.delta" which does what I want but isn't very elegant. I have consulted the R documents, MASS, and S Programming. Is there a practical way to optimize the code? Thank you very much. Peter B. Function: eval.delta <- function(delta){ cat("VALUES\n") vlr <- NULL k <- 0 for(j in 1:length(delta)) if(delta[j] <= 2){