search for: newdata1

Hi all - my first time here and am having an issue with the Predict function. I am using a tutorial as a guide, locate here: http://www.ats.ucla.edu/STAT/R/dae/mlogit.htm My code gives this error > newdata1$predicted <- predict(mlogit,newdata=newdata1,type="response") Error in `$<-.data.frame`(`*tmp*`, "predicted", value = c(0.332822934960197, : replacement has 810 rows, data has 6 How can I resolve this problem so I can just predict values for the supplied matrix(newdat...

...) data set ("data") using logistic regression (glm): logreg1 <- glm(z ~ x1 + x2 + y, data=data, family=binomial("logit"), na.action=na.pass) Then, I created a data frame with 2 fixed levels (0 and 1) for each predictor: attach(data) x1<-c(0,1) x2<-c(0,1) y<-c(0,1) newdata1<-data.frame(expand.grid(x1,x2,y)) names(newdata1)<-c("x1","x2","y") Finally, I calculated model-predicted probabilities for each combination of those fixed levels: newdata1$predicted <-predict(logreg1,newdata=newdata1, type="response") I am pretty...

...a simpler example: I have Centre<- matrix(c(0,1,0,1), nrow=2) # the two created centres in a two dimentional case are Centre [,1] [,2] [1,] 0 0 [2,] 1 1 NewData<-rbind(matrix(rnorm(100, sd = 0.3), ncol = 2), matrix(rnorm(100, mean = 1, sd = 0.3), ncol = 2)) NewData1<-cbind(c1:100), NewData) colnames(NewData1)<-c("ID","x","y") # my data head(NewData1) ID x y [1,] 1 -0.3974660 0.1541685 [2,] 2 0.5321347 0.2497867 [3,] 3 0.2550276 0.1691720 [4,] 4 -0.1162162 0.6754874 [5,] 5 0.1570996 0.117...

...obtain the estimates of b0, b1 and b2 by industry and year (for example I need to have de b0 for industry 20 and year 2000, for industry 20 and year 2001...). Then I need to calculate the fitted values and the residuals by firm so I need to keep b0, b1 and b2 in a way that I could do something like newdata1<-transform(final3,Y'=b0+b1.X+b2.Z) newdata2<-transform(newdata1,residual=Y-Y') or another way to keep Y' and the residuals in a dataframe with the columns firm and year. Until now I have been doing this in very hard way and because I need to do it several times, I need your hel...

Dear all, I have a matrix, called newdata1, > dim(newdata1) [1] 34176 83 It looks like: EntrezID Name S1 S2 S3 S4 S5..... 1 4076 CAPRIN1 0.1 0.2 0.3... 2 139170 WDR40B 0.4 0.5 0.6... 3 5505 PPP1R2P1 0.3 0.3 0.7... 4 4076 CAPRIN1 0.7...

Dear R Wizards, After much frustration and days of confusion I have finally broken down and am asking for help, which I don’t like doing, but I just can’t figure this one out on my own. I’ve conducted a laboratory experiment testing the effects of temperature and salinity on whether or not a biological event will occur (Go or NoGo). I’ve coded the factors temperature and salinity as factors for

Hello! I have a matrix: > dim(data1) [1] 34176 581 of 34176 rows and 581 columns, I want to make a new matrix data2 by taking the 2nd column, 9th column, 16th column.... the column number is in the order of: 2 9 (2+7) 16 (9+7) 23 (16+7) ... the new matrix data2 should include 83 columns, is there an easy way to do that using cbind() function? Thanks a lot! Allen [[alternative HTML

...rm 2) year firm x 1 2001 1 11 2 2002 1 22 3 2003 1 32 4 2004 1 25 5 2005 1 26 6 2004 2 98 7 2005 2 101 8 2001 3 14 9 2002 3 87 10 2003 3 56 Second, I need to create a new variable that is the lagged value of x. I''ve done newdata1<-transform(data1,y=lag(x,1)) But it doesn''t work. I also need to create a new variable that is the opposite of lag(). I''ve done newdata2<-transform(data1,z=lag(x,-1)) But, of course, it doesn''t work neither. Thank you for all your help. Cecília Carmo...