similar to: Is there an equivalent * operator?

Hi all, I am very confused with class. I am looking at some weather data which I want to use as explanatory variables in an lm. R has treated these variables as factors (i.e. with different levels), whereas I want them treated as discretely measured continuous variables. So I need to reassign the class of these variables, right? Indeed, doing class(southwest$pressure) (pressure being air

Hi all, Firstly I appologise if this question has been answered previously, however searching of the archives and the internet generally has not yielded any results. I am looking in to the effects of summer weather conditions (temperature, humidity etc), on the incidences of a breathing disorder brought on through smoking (COPD). I am fairly new to R and completely new to the idea of

Hi, Appologies for the simple nature of this question, I am unable to find the answer in manuals (EG and introduciton to R). I have written a function in a text editor and saved it with an .R extension. It is saved in my working directory. How can I run it, do I need to use source? If so, how do I supply the arguments to the function? Or does it need to be saved in a particular directory?

Dear all, I am having difficulties using the seemingly-simple function lag. I have a dataframe with several weather variables (maxitemp, windspeed, rainfall etc), and the response variable (admissions). The dataset is fairly large (1530 observations). I simply want to model the response against a lag of a couple of the explanatory variables, say maxitemp and rainfall. I would like to look at

Dear all, I appologise for cluttering up the list with such a basic question, however I have been unable to find the answer I want (possibly through my poor usage of the R help system). As I am visually impaired and using assistive technology, I think I would prefer to use R from the terminal mode, i.e. by running rterm.exe found in the bin directory. I have managed to set my working

Hi all, Thanks for the help with my previous post. I have just two more questions for the minute. I think I said in a previous post that I like to use the terminal, i.e. run rterm.exe. On exiting the terminal, I am asked if I want to save the workspace. If I hit y (yes), the workspace is just saved as .rdata in my working directory, does anyone know how I can name it directly from the

Hi, I have eight vectors that I would like to orthogonalize preferably using R. The vectors are of considerable length, however due to their nature I know they satisfy the conditions needed to apply the Gram-Schmidt algorithm. Before I embark on some R coding, I wanted to check that there is no facility / function already around that computes the orthogonalized set of vectors? I have performed

Hi, Is there a function in R to calculate the coefficient of skewness of some data? I had expected there to be one, but can find no information about it. Thanks for any pointers. Robin Williams Met Office summer intern - Health Forecasting robin.williams@metoffice.gov.uk [[alternative HTML version deleted]]

Hi, Is there any quick and easy way to rename a number of objects, without having to rename each one individually and then remove the old one? And if so, is there anything I can do to adjust the associated comments accordingly? Thanks for any help, Robin Williams Met Office summer intern - Health Forecasting robin.williams@metoffice.gov.uk [[alternative HTML version deleted]]

Hi, I am looking for a normality test in R to see if a vector of data I have can be assumed to be normally distributed and hence used in a linear regression. > help.search("normality test") suggests the Shapiro test, ?shapiro.test. Now maybe I am interpreting things incorrectly (as is usually the case), am I right in assuming that this is a composite test for normality, and hence a

Hi, Please could someone explain how this element of predict.lm works? From the help file ` newdata An optional data frame in which to look for variables with which to predict. If omitted, the fitted values are used. ' Does this dataframe (newdata) need to have the same variable names as was used in the original data frame used to fit the model? Or will R just look across consecutive

Hi all, When using lm to model a response with 8 explanatory variables, one of the variables is not defined due to "singularities". I have checked the csv file from which the data come, there are no na's in the dataset, etc. What should I be looking for in this variable to correct the problem? Thanks for any help. Robin Williams Met Office summer intern - Health Forecasting

Hi all, please, someone can explain me how update my R version? thank you! giov -- View this message in context: http://www.nabble.com/R-update-tp19291451p19291451.html Sent from the R help mailing list archive at Nabble.com.

Hi there, I have a dataset stored in an object which has very huge volume of rows.I want to reuse it for comparing with other datasets.I dont want it to reload every time i run the script.Is there a way of saving a particular loaded object in the workspace and reusing it. Kindly help me. Ramya Thulasingam -- View this message in context:

Hi, After manipulate my data I have ended up with 5 different data frames with different number of observations but the same number of variables (columns) An example, if I write str(object1), I see this, data.frame': 47 obs. of 3 variables: $ ORF : Factor w/ 245 levels "YAL038W","YAL054C",..: 10 19 38 39 44 45 50 51 59 60 ... $ mRNA : num 0.891 1.148 1.202

Hi, Is there any facility in R to perform a stepwise process on a model, which will remove any highly-correlated explanatory variables? I am told there is in SPSS. I have a large number of variables (some correlated), which I would like to just chuck in to a model and perform stepwise and see what comes out the other end, to give me an idea perhaps as to which variables I should focus on. Thanks

Hi, if I got it right then the survival-time we expect for a subject is the integral over the specific survival-function of the subject from 0 to t_max. If I have a trained cox-model and want to make a prediction of the survival-time for a new subject I could use survfit(coxmodel, newdata=newSubject) to estimate a new survival-function which I have to integrate thereafter. Actually I thought

Hello, Firstly let me explain that the nature of what I want to do is actually beyond my statistical knowledge, having only taken a second year university stats course last year. Therefore I may have missed the statistical essence of what I want to do as well as my lack of ability to do it in R. I am trying to fit some hospital admissions data to a series of weather variables. Due to my lack of

Hi useR's I have created a simple map of the world using the following code: m <- map(xlim=c(-180,180), ylim=c(-90,90)) map.axes() I then create a grid of dimension 36x72 using the code: map.grid(m, nx=72, ny=36, labels=FALSE, col="black") This gives 2592 grid cells. In a separate data set of dimension 36x72, I have 2592 temperature values (some missing values are present)

Hi all, I have a large data.frame, 1530 observation with 6 columns. I want to merge a 7th column, a transformation of the response variable (hospital admissions), namely trans<-sqrt(copd$admissions+0.25) trans<-data.frame(trans) And now when I do copd2<-merge(copd,trans) (copd being my original data.frame), R either crashes or is taking an extremely long time to do the computation. I