similar to: What to do with this data?

http://www.nabble.com/file/p14668788/paragraphs.png Hi, R is is world full of wonders... I created the attached plot, and I think it's exactly what I need! Well, actually I think it is more that wht I need... I wanted R to show the mean values of the categories on the x-axis and maybe the standard derivation as well. I am pretty confident that the bold horrizontal lines in the plot show

http://www.nabble.com/file/p16349649/at-length.png Hi, I produced this graph with R and I am very happy with it. But now I wonder: Is this some standard way of displaying data and if so, does it have a name? (like Histogram, Box plot etc.) I need to explain the plot to people so knowing a bit more about what exactly this is, would certainly help ;-) Thanks a lot! -- View this message in

Hi all, I'm running R version 2.9.2 on a PC. I'm having a problem with a loop, and have tried using an if statement within to fix it, but to no avail. Any advice would be appreciated. Here is my code: ***************************************************** eblest <- function(i,dir, sterr, weight, aux) { n <- nrow(dir) Y <- as.matrix(dir[,i], ncol=1) sigma2ei <-

http://www.nabble.com/file/p14664173/at-modality.png I created the above image with R and I have one problem left: Some of the labels of the axes do not show up, probably because there's not enough space. I use the following code to create the plot: modality <- read.table("results.table", header=TRUE, sep=",") color <-

#I have these data. Basically, I want to run a tapply to calculate the mean and st. err. by factor. #The problem is, I want to add a finite correction to the variance prior to calculating the standard error. #Now I know I could just do this in 3/4 steps by calculating the var, applying the correction, then calculating the StErr. #However, I am trying to learn about functions and how they work. So

https://bugzilla.samba.org/show_bug.cgi?id=13147 Bug ID: 13147 Summary: inconsistent behaviour regaring vanished files information Product: rsync Version: 3.0.9 Hardware: x64 OS: Mac OS X Status: NEW Severity: minor Priority: P5 Component: core Assignee:

Hi! When checking validity of a model for a large number of experimental data I thought it to be interesting to check the information provided by the summary method programmatically. Still I could not find out which method to use to get to those data. Example (not my real world data, but to show the point): [BEGIN] > DNase1 <- subset(DNase, Run == 1) > fm1DNase1 <- nls(density ~

Hello, I think this might be a beginner question, but I couldn't find the answer in the manual... http://www.nabble.com/file/p14618947/at-modality.png I created this image with R by using the following code: modality <- read.table("results.table", header=TRUE, sep=",") color <-

Hi, I have to read in data which looks like this: SeriesA, 5, 5, 5, 5 SeriesB, 8, 5, 8, 8, 7, 10, 2, 7, 3 SeriesC, 5, 5, 8, 4, 7, 7, 4, 5 SeriesD, 5, 9, 5, 4, 2, 3, 10, 1 SeriesE, 7, 10, 9, 5, 8, 6, 10, 9, 5, 10, 4, 3, 2, 10, 8, 8, 10, 10, 10 SeriesF, 1, 2, 1, 5, 1, 7, 5, 7, 7, 3 There are actually much more data points in the data, each line contains between 300 and 500 values. If I use

I?m trying to run a logistic joinpoint regression utilising the ljr package. I?ve been using the forward selection technique to get the number of knots for the analysis, but I?m uncertain as to my results and the interpretation. The documentation is rather brief ( in the package and the stats in medicine article is quite technical) and without any good examples. At the moment I?m thinking 1)find

Hi guys, I''m facing an error trying to run my app as mongrel_service, hope those who have faced similar issue can help to shed some lights. The app was fine when running from console, but when running it as a service, it failed when I try to upload ''image file'', it has no issue uploading other types of files. Environment: ------------ mongrel (1.0.1, 0.3.13.3)

Hello, I''m running mongrel behind apache via proxypass. Every now and then, a spammer tries to proxy traffic through apache, and for some reason, apache forwards the request to mongrel, even though it''s not a site being hosted by me. At times this seems to cause mongrel to become unresponsive, and all requests to the site then fail with a proxy error until mongrel is

Hello, I am trying to fit gamma, negative exponential and inverse power functions to a dataset, and then test whether the fit of each curve is good. To do this I have been advised to calculate predicted values for bins of data (I have grouped a continuous range of distances into 1km bins), and then apply a chi-squared test. Example: > data <- data.frame(distance=c(1,2,3,4,5,6,7),

Hi All, I am illustrating a simple, two-way ANOVA using the following data and I'm having difficulty in expressing the predicted values succinctly in R. X<- data.frame(read.table(textConnection(" Machine.1 Machine.2 Machine.3 53 61 51 47 55 51 46 52 49 50

Hello I carried out a logistic regression and found predicted values. Then I want to see both predictors (var1,var2..) and predicted values in same matrix. In other words, I need to know each combinations and predicted values. I used: cbind(var1,var2,var3,var4,predict(glm.obj,type="resp")) I got a somewhat strange result: var1 var2 var3 var4 var5 var6 predicted vals ------

Hi, the standard errors of the coefficients in two regressions that I computed by hand and using lm() differ by about 1%. Can somebody help me to identify the source of this difference? The coefficient estimates are the same, but the standard errors differ. ####Simulate data happiness=0 income=0 gender=(rep(c(0,1,1,0),25)) for(i in 1:100){ happiness[i]=1000+i+rnorm(1,0,40)

Dear List, I would like to calculate the Goodman-Kruskal gamma for the predicted classes obtained from an ordinal regression model using lrm in the Design package. I couldn't find a way to get gamma for predicted values in Design so have found previous positings suggesting to use : Rcorr.cens(x, S outx = TRUE) in the Hmisc package My question is, will this work for predicted vs

Hello, Much clearer now, thanks. It's a matter of changing the function boot calls to return the predicted values at the point of interess, education = 50, income = 75. I have changed the way the function uses the indices a bit, the result is the same, it's just the way I usually do it. pred.duncan.function <- function(data, indices) { mod <- lm(prestige ~ education +

Hi: # How can I extract the 'Forecasts' from the 'summary(predicted)' from the example below? library(forecast) weightData <- data.frame(weight = c(2.1,2.4,2.8,3.6,4.1,5.2,6.3),week= 1:7) weight <- as.numeric(weightData$weight) predicted <- forecast(weight,h=3,level=95) # see the predicted summary(predicted) # I would like to extract the three predicted values and #

Dear R helpers, running the following code of a glm model of the family poisson, gives predicted values < 0. Why? library(MASS) library(stats) library(mvtnorm) library(pscl) data(bioChemists) poisson_glm <- glm(art ~ fem + mar + kid5 + phd + ment, data = bioChemists, family = poisson) predicted.values = predict(poisson_glm) range(predicted.values) Thank you in advance for any hints.