similar to: Plotting residuals from a sem object

Hi Group, Create some example data. set.seed(1) wide_data <- data.frame( id=c(1:10), predictor1 = sample(c("a","b"),10,replace=TRUE), predictor2 = sample(c("a","b"),10,replace=TRUE), predictor3 = sample(c("a","b"),10,replace=TRUE), measurement1=rnorm(10), measurement2=rnorm(10)) head(wide_data) id

R-help: I am trying to decide between using a multiple linear regression or a linear mixed effects model for my data: model1 <- lm (responsevariable ~ predictor1 + predictor2 + predictor3 + predictor4, data= data) model2 <- lme (responsevariable ~ predictor1 + predictor2 + predictor3 + predictor4, random = ~1 | site, data= data) anova (model1, model2) but I keep getting the

I am using the gbm package for generalized boosted regression models, and would like to be able to extract the coefficients produced for storage in a database. I am already using R to automatically generate formulas that I can export to a database and store. For example, I have been using Dr. Harrell's lrm package to perform logistic regression, e.g.: output <-

Hi, I use a mboost model to predict my dependent variable on new data. I get the following warning message: In bs(mf[[i]], knots = args$knots[[i]]$knots, degree = args$degree, : some 'x' values beyond boundary knots may cause ill-conditioned bases The new predicted values are partly negative although the variable in the training data ranges from 3 to 8 on a numeric scale. In order to

Hi, I would like to combine multiple xyplots into a single, multipanel display. Using R 3.0.1 in Ubuntu, I have used c() from latticeExtra to combine three plots, but the x-axis for two plots are on a log scale and the other is on a normal scale. I also have included equispace.log=FALSE to clean up the tick labels. However, when I try all of these, the x-axis scale of the first panel is used

I have built a Kalman Filter model for flu forecasting as shown below. Y - Target Variable X1 - Predictor1 X2 - Predictor2 While forecasting into the future, I will NOT have data for all three variables. So, I am predicting X1 and X2 using two Kalman filters. The code is below x1.model <- dlmModSeas(52) + dlmModPoly(1, dV=5, dW=10) x2.model <- dlmModSeas(52) + dlmModPoly(1, dV=10,

Hi all, I am trying to fit an ANOVA model in R using the aov/lm commands. I have a set of observational (i.e. no fixed experimental effects) data, in which I have identified high and low clusters of the response variable. The design is unbalanced, with 773 high cluster observations, and 523 low cluster observations. I would like to test a set of 7 correlates to see if there are significant

I was unsure of what suitable goodness-of-fit tests existed in R for logistic regression. After searching the R-help archive I found that using the Design models and resid, could be used to calculate this as follows: d <- datadist(mydataframe) options(datadist = 'd') fit <- lrm(response ~ predictor1 + predictor2..., data=mydataframe, x =T, y=T) resid(fit, 'gof'). I set up a

>From http://bugs.r-project.org/cgi-bin/R: If you are not sure whether you have observed a bug or not, it is a good idea to ask on the mailing list R-Help by sending an e-mail to r-help at stat.math.ethz.ch rather than submitting a bug report. I'm wondering whether to submit a bug report on this: ============================================================== >

Hello, I came across a problem when building a randomForest model. Maybe someone can help me. I have a training- and a testdataset with a discrete response and ten predictors (numeric and factor variables). The two datasets are similar in terms of number of predictor, name of variables and datatype of variables (factor, numeric) except that only one predictor has got 20 levels in the training

I am trying to print a graph > plot(y=atestplot$b,x=atestplot$a, type="s") > win.print() This leads to a windows print dialog box- that diappears when i hit print. subquently i find a "GraphAppJob" of zero size in the print queue- this just sits until I enter dev.off() at which point a blank sheet is printed Is it me or is this a bug? Incidentally if i just

Hi, I'm getting to grips with using R to perform repeat measures analysis of variance and was wondering is there a potted method to obtain Huynh and Feldt or other adjustments for sphericity violations? Thanks Dominic Dr Dominic J Barraclough Dept Neurobiology and Anatomy, University of Rochester, 601 Elmwood Av, Box 603, Rochester NY 14642 tel (716) 2753627 dominic_barraclough at

Hi, [System info: R 1.6.1 compiled from source (no args to configure) on Redhat 7.1 Linux i/386] I have some spatial statistics programs that recently (since R 1.6.1) have generated SIGSEGV. These R programs use the splancs library as well as some C code of my own for Voronoi analysis. The program has a big loop to fit various model parameters against a spatial distribution of biological

Hi, I am trying to use CART to find an ideal cut-off value for a simple diagnostic test (ie when the test score is above x, diagnose the condition). When I put in the model fit=rpart(outcome ~ predictor1(TB144), method="class", data=data8) sometimes it gives me a tree with multiple nodes for the same predictor (see below for example of tree with 1 or multiple nodes). Is there a way

Dear Fellows, I would like to know how to uncompress a gz file at the R console. I could not find out any help from the R-help archive. Thanks for your great help. Best Regards, Wonsang You ----- -- Wonsang You Special Lab Non-Invasive Brain Imaging Leibniz Institute for Neurobiology http://www.ifn-magdeburg.de -- View this message in context:

Dear fellows, I am a novice in R. I would like to combine a matrix and a vector. Assume that we have the matrix a and the vector b with same length of column. a<-matrix(seq(1:10),nrow=2,ncol=5,byrow=TRUE) a= 1 2 3 4 5 6 7 8 9 10 b<-t(c(11,12,13,14,15)) b= 11 12 13 14 15 Then, I want to combine a and b as follows. c= 1 2 3 4 5 6 7 8 9

Dear R Helpers, I have searched for any R package or code for simulating multivariate fractional Brownian motion (mFBM) or multivariate fractional Gaussian noise (mFGN) when a covariance matrix are given. Unfortunately, I could not find such a package or code. Can you suggest any solution for multivariate FBM and FGN simulation? Thank you for your help. Best Regards, Ryan ----- Wonsang You

Hello, I'd appreciate any ideas on how to compare the skewness of two samples. In my case, one sample is likely to be roughly normal and the other one skewed. I could run two D'Agostino tests, but then I'll have to correct for the family-wise error. What if both samples are skewed? If there are no general tests (or they can't exist), I'd like to know. Thanks, Skirmantas

Dear R-Helpers, I want to try the 2D (two-dimensional) convolution in R. For example, let us we have the following kernel and data. kernel <- (1,2,3,2,1) data <- array(1:100, dim=c(10,10)) I know the function 'convolve' only for one-dimensional convolution, but it is just for a 1D sequence. Is there any function for 2D convolution? For theory, please refer to the following link:

Hello, Does anyone know of an R package that can read Windows BMP format images? Many thanks, Greg Jefferis. -- Gregory Jefferis, PhD Division of Neurobiology MRC Laboratory of Molecular Biology, Hills Road, Cambridge, CB2 0QH, UK. http://www2.mrc-lmb.cam.ac.uk/group-leaders/h-to-m/g-jefferis