similar to: Odd r-squared

Hi all, I have a package that is specific to a task I was repetitively using a few years ago. I now needed to run it again with new data. However I am told it was built with an older version or R and will not work. How can I tweak the package so it will run on 11.1? It was a one-off product and has not been maintained. Is there a way to "unpackage" it and repackage it to work? I

Hello R-Users,   I have one binary dependent variable and a set of independent variables (glm(formula,…,family=”binomial”) ) and I am using the function stepAIC (“MASS”) for choosing an optimal model. However I am not sure if stepAIC considers significance properties like Likelihood ratio test and Wald test (see example below).     > y <- rbinom(30,1,0.4) > x1 <- rnorm(30) > x2

Dear R People: Suppose I have the following data frame: x1 x2 x3 1 -0.1582116 0.06635783 1.765448 2 -1.1407422 0.47235664 0.615931 3 0.8702362 2.32301341 2.653805 > str(xx) 'data.frame': 3 obs. of 3 variables: $ x1: num -0.158 -1.141 0.87 $ x2: num 0.0664 0.4724 2.323 $ x3: num 1.765 0.616 2.654 I can exclude the second column nicely via: >

Hi, I've sent that patch once already but it seems more or less forgotten in the tumultuous days of the latest vulnerability. It adds a new define NO_IPPORT_RESERVED_CONCEPT which can be defined on platforms not supporting the concept of "privileged" ports only accessible by privileged users but which allow everyone to use these ports. This patch removes some Cygwin dependencies

Hi. I am currently trying to run some Spearman correlations, and have encountered two issues. 1) When using cor.test() with a variable that includes ties, I get the "Cannot compute exact p-values with ties" error. I have read that this function now uses an asymptotic formula that allows for ties, so do not understand why I am getting this error. (I am running version 2.4.0.) I

Dear all, this is probably more a statistics question than an R question but probably there is somebody who can help me nevertheless. I'm running a regression with four predictors (a, b, c, d) and all their interaction effects using lm. Based on theory I assume that a influences y positively. In my output (see below) I see, however, a negative regression coefficient for a. But several of the

Hi, I am wondering if there is a way to display the full anme of the regression coeffients/factors in the summary? Suppose I have a bogus data set using weekday as factor which has 7 levels such as: mydata <- sample(364) wk <- rep(1:7, 52) weekday <-

I am trying to do a priori ANOVA analysis for a class assignment. The professor uses SPSS and does not know R. I want to do a simple planned comparison but have been unable to find a function or specific help. There is a grouping variable with five levels and a subsequent response variable. I also created a few columns that contain my group contrasts to see if anything could come of that. My first

Using rsync 2.6.0 on both ends, I ran rsync -v --files-from files andrew@pimlott.net: . and got an error from the remote rsync. The reason is that the remote rsync is run as rsync --server --sender -vvR --files-from=- --from0 . which conflicts with a check in options.c that rsync must have two non-option arguments when --files-from is used. I tried again with the latest nightly

Hi, I am generating large Kac matrices (also known as Clement matrix). This a tridiagonal matrix. I was wondering whether there is a vectorized solution that avoids the `for' loops to the following code: n <- 1000 Kacmat <- matrix(0, n+1, n+1) for (i in 1:n) Kacmat[i, i+1] <- n - i + 1 for (i in 2:(n+1)) Kacmat[i, i-1] <- i-1 The above code is fast, but I am curious about

Tim Legge has passed the following message on to me: hpa wrote: > Quinn wrote: > > Now it seems I have found a bug in PXELINUX with regards to etherboot. > > Up until 2.07 pxelinux was responsive to the keyboard. From 2.08 and > > up the keyboard is locked at the boot prompt when pxelinux is loaded > > via etherboot 5.3.14. > > That would not be a PXELINUX bug,

Hi, R-users, data is a matrix like this AMR BS GE HR MO UK SP500 1974 -0.3505 -0.1154 -0.4246 -0.2107 -0.0758 0.2331 -0.2647 1975 0.7083 0.2472 0.3719 0.2227 0.0213 0.3569 0.3720 1976 0.7329 0.3665 0.2550 0.5815 0.1276 0.0781 0.2384 1977 -0.2034 -0.4271 -0.0490 -0.0938 0.0712 -0.2721 -0.0718 1978 0.1663 -0.0452 -0.0573 0.2751 0.1372 -0.1346

Sorry. Let me try again then. I am trying to find "significant" predictors" from a list of about 44 independent variables. So I started with all 44 variables and ran drop1(sep22lr, test="Chisq")... and then dropped the highest p value from the run. Then I reran the drop1. Model: MIN_Mstocked ~ ORG_CODE + BECLBL08 + PEM_SScat + SOIL_MST_1 + SOIL_NUTR + cE + cN +

Hi All I can specify whatever inits, it has no effect on the estimation. I am replicating a textbook example. The result is completely trash, having estimates of -58.7 (sd=59.3), where it should be closer to an ml estimate of 0.585 (SE=0.063). The two chains within one run are different, but with different inits for different runs, I get exactly the same chains, and I mean exactly. If I set

Dear all, How do I make R show the R-squared (deviance explained by the model) in a logistic regression? Below is how I write my syntax. Basically I want to investigate density-dependence in parasitism of larvae. Note that in the end I perform a F-test because the dispersion factor (residual deviance / residual df) is significantly higher than 1. But how do I make R show the

Hi, I have a few hundreds files with numerical information of different length but with the same column structure. I use the following code to get summary statistics fplist <- list.files(pattern=".*analysis") for (fp in fplist){ x2 <- read.delim(fp) summary(x2) } Summary gives something like: summary (x2) V1 V2

Hello. I'm a new user of R, and I have a question regarding the use of aov and lm-functions. I'm doing a fractional factorial experiment at our production site, and I need to familiarize myself with the analysis before I conduct the experiment. I've been working my way through the examples provided at http://www.itl.nist.gov/div898/handbook/pri/section4/pri472.htm

Hi All, simple question: do you know how to graph the following object/matrix in a 'surface manner': [,1] [,2] [,3] [,4] [,5] [,6] [1,] -0.154 -0.065 0.129 0.637 0.780 0.221 [2,] 0.236 0.580 0.448 0.729 0.859 0.475 [3,] 0.401 0.506 0.310 0.650 0.822 0.448 [4,] 0.548 0.625 0.883 0.825 0.945 0.637 [5,] 0.544 0.746 0.823 0.877 0.861 0.642 [6,] 0.262 0.399

Trying to do a meta-analysis of correlations in R using the meta package; have tried several things and keep getting a similar error. Can anyone help explain the error? > cor<-c(-0.3018, 0.667, -3.8002, -0.607, -0.4885, -3.8002, -0.0701, 0.1348, -0.9505, -0.5709, -0.6127, -1.2419, -0.1511, -0.1054)> n<-c(3,4,3,3,3,3,16,36,30,9,3,3,30,4)> library(meta)> metacor(cor, n, data=NULL,

Two time series questions: FITTING TRANSFER FUNCTIONS WITH LAGS: Consider the following toy example: > dates <- paste(11:21, "/01/2005", sep="") > Dates <- as.Date(dates, "%d/%m/%Y") > set.seed(1) > DF <- data.frame(date=Dates, y=rnorm(11), x=rnorm(11, 3)) > arima(DF$y, c(1,0,0), xreg=lag(DF$x, 1)) ar1 intercept lag(DF$x,