search for: mses

...ng problem to my attention. The code is abstracted from the appendix on mixed models from my R and S-PLUS Companion: > set.seed(12345) # for reproducibility > library(nlme) Loading required package: lattice > data(MathAchieve) > data(MathAchSchool) > attach(MathAchieve) > mses <- tapply(SES, School, mean) > detach(MathAchieve) > Bryk <- as.data.frame(MathAchieve[, c("School", "SES", "MathAch")]) > names(Bryk) <- c("school", "ses", "mathach") > sample20 <- sort(sample(7185, 20)) >...

...ut on here, but I am having trouble with my R code. I am trying to get the p-values, R^2s etc for a number of different groups of variables that are all in one dataset. This is the code: #Stand counter st<-1 #Collections stands<-numeric(67) slopes<-numeric(67) intercepts<-numeric(67) mses<-numeric(67) rsquares<-numeric(67) pValues<-numeric(67) #Start lists for X and Y values within each stand xi<-numeric(0) yi<-numeric(0) #Set the first element to the starting X and Y values xi[1]=X[1] yi[1]=Y[1] #Start looping working through your data, record by record for (i in 2:l...

Can I ask a small stat. related question here? Suppose I have two predictors for a time series processes and accuracy of predictor is measured from MSEs. My question is, if two predictors give same MSE then, necessarily they have to be identical? Can anyone provide me any counter example? Thanks. -- View this message in context: http://www.nabble.com/A-stat-related-question-tp25505618p25505618.html Sent from the R help mailing list archive at Nab...

Dear R list members, I've turned up a strange discrepancy between results obtained from the lme function in the nlme package in R and results obtained with lme in S-PLUS. I'm using version 3.1-24 of nlme in R 1.4.1 under Windows 2000, and both S-PLUS 2000 and 6.0, again under Windows 2000. I've noticed discrepancies in a couple of instances. Here's one, using data from Bryk

...rsion 2 or later This version (3.4-1) contains bug fixes as well as some additional features: o Error rates or MSE are returned as a vector, so one can examine how they change as number of trees increases. o Added a plot() method for randomForest objects, which plots the error rates or MSEs. o Added var.imp.plot() to plot the variable importance. o Added partial.plot() for visualizing marginal effect of a predictor variable in regression. o Added functions grow() and combine(), which can be used to aggregate several randomForest objects into one. This can be useful, e....

Hi, I'm performing (blocked) 10-fold cross-validation of a several time series forecasting methods, measuring their mean squared error (MSE). I know that the MSE_cv is the average over the 10 MSEs. Is there a way to calculate the standard error as well? The usual SD/sqrt(n) formula probably doesn't apply here as the 10 observations aren't independent. Thanks, Gad -- Gad Abraham Department of Mathematics and Statistics The University of Melbourne Parkville 3010, Victoria, Austra...

My son is taking some programming courses in school and it would be very helpful if he could run Visual Studio on his Mac. I own older VB5 and Visual Studio 6 (from my old PC days). [Embarassed] I cannot figure out how to install Wine on his Mac. Can someone please guide me (e.g. show me all the steps I need to follow to install Wine) so that I can then install VB5 and VS6? He's not

> importance(rfor.pdp11_t25.comb1,type=1) %IncMSE v1 -0.28956401263 v2 1.92865561147 v3 -0.63443929130 v4 1.58949137047 v5 0.03190940065 I wasn't entirely confident with interpreting these results based on the documentation. Could you please interpret? [[alternative HTML version deleted]]

Hello, I am randomly generating values and then using an ANOVA table to find the mean square value. I would like to form a loop that extracts the mean square value from ANOVA in each iteration. Below is an example of what I am doing. a<-rnorm(10) b<-factor(c(1,1,2,2,3,3,4,4,5,5)) c<-factor(c(1,2,1,2,1,2,1,2,1,2)) mylm<-lm(a~b+c) anova(mylm) Since I would like to use a loop to

...points (and their noise) and other coefficients depend on N2 data points (and their noise). (and I don't think lm would given me an aswer with such bifurcated Sincerely, Leif S. Kirschenbaum, Ph.D., PMP, CRE * In reality I will perform both quadratic and linear fits on N1 and N2, compare MSEs of the quadratic vs. linear on N1 to determine the best fit for N1 points and similarly on N2. The situation is that I am measuring many instances of an object (~16,000 devices per wafer) whose behavior is not well modelled at room temperature. By inspection of ~4,000 plots of device data I see t...

Dear Researches, I am using RF (in regression way) for analize several metrics extract from image. I am tuning RF setting a loop using different range of mtry, tree and nodesize using the lower value of MSE-OOB mtry from 1 to 5 nodesize from1 to 10 tree from 1 to 500 using this paper as refery Palmer, D. S., O'Boyle, N. M., Glen, R. C., & Mitchell, J. B. O. (2007). Random Forest Models

Hello, I've managed to get LLVM 1.8 to build properly with MSVC8 with some effort. Most of the changes necessary were very minor C++ usage issues; for instance, VC8 can't deal with prototyping something that's really a class as 'struct Foo;' or vice versa (it creates issues with matching function signatures during linking.) Additionally, I had to do quite a few updates to the