similar to: dependency ‘Matrix’ is not available when installing Rcmdr

Unbuntu 10.04 R 2.10 I am trying to install Rcmdr and receive the following messages: The downloaded packages are in ?/tmp/RtmpzhjDZG/downloaded_packages? Warning messages: 1: In install.packages("Rcmdr", dependencies = TRUE) : installation of package 'Rmpi' had non-zero exit status 2: In install.packages("Rcmdr", dependencies = TRUE) : installation of package

Fedora 10 R 2.8.1 I hope someone can tell me the meaning of error I received trying to install RODBC and how I can get around the problem. n.b. The error originally occurred then I was installing Rcmdr. I then tried to install RODBC separately and received the same error. checking sql.h usability... no checking sql.h presence... no checking for sql.h... no checking sqlext.h usability... no

R 2.8.1 Windows XP Fedora Linux. I would like a suggestion for an editor that will help format my R code that can be used with Rcmdr. Is there anything I need to know about running or installing an editor when using Rcmdr? I run R on both Windows and Linux (Fedora). Thank you, John John David Sorkin M.D., Ph.D. Chief, Biostatistics and Informatics University of Maryland School of Medicine

Windows Vista R 2.9.1 When trying to install Rcmdr I get the message shown below. What does it mean, do I need to do anything? The downloaded packages are in C:\Users\John Sorkin\AppData\Local\Temp\RtmpRCLbhe\downloaded_packages updating HTML package descriptions Warning message: In file.create(f.tg) : cannot create file 'C:\PROGRA~1\R\R-29~1.1/doc/html/packages.html', reason

I am having trouble selecting rows of a dataframe that will be included in a regression. I am trying to select those rows for which the variable Meno equals PRE. I have used the code below: difffitPre<-lm(data[,"diff"]~data[,"Age"]+data[,"Race"],data=data[data[,"Meno"]=="PRE",]) summary(difffitPre) The output from the summary indicates that

Is there an R function that can be used to calculate a sample size for a linear regression: i.e. Given a linear regression: y=f(x,z) i.e. fit1<-lm(y~x+z) is there a function which can be passed coef(z), SE(z), and other parameters to determine a sample size based on z, SEz and other information from the regression? Thanks, John John Sorkin M.D., Ph.D. Chief, Biostatistics and Informatics

David, predict.glm and se.fit were exactly what I was looking for. Many thanks! John John David Sorkin M.D., Ph.D. Professor of Medicine Chief, Biostatistics and Informatics University of Maryland School of Medicine Division of Gerontology and Geriatric Medicine Baltimore VA Medical Center 10 North Greene Street GRECC (BT/18/GR) Baltimore, MD 21201-1524 (Phone) 410-605-7119 (Fax)

> On Oct 22, 2017, at 5:01 PM, Sorkin, John <jsorkin at som.umaryland.edu> wrote: > > David, > Again you have my thanks!. > You are correct. What I want is not technically a contrast. What I want is the estimate for "regional" and its SE. There needs to be a reference value for the contrast. Contrasts are differences. I gave you the choice of two references

R 2.7.2 Windows XP I am using apply to compute a series of Student's t-test from two matrices, sample1 and sample2. boo<-apply(sample1,1,t.test,sample2) I want to pick of the p-values from the tests, but can't seem to get it to work. I have tried several methods to get the values including: boo<-apply(sample1,1,t.test$t.test,sample2) boo<-apply(sample1,1,t.test,sample2)$t.test

I am trying to drop rows of a dataframe based on values of the column PID, but my strategy is not working. I hope someoen can tell me what I am doing incorrectly. # Values of PID column > jdata[,"PID"] [1] 16608 16613 16355 16378 16371 16280 16211 16169 16025 11595 15883 15682 15617 15615 15212 14862 16539 [18] 12063 16755 16720 16400 16257 16209 16200 16144 11598 13594 15419 15589

R 2.2.0 windows XP How can I perform a regression analyses using a vector of means, a variance-covariance matrix? I looked at the help screen for lm and did not see any option for using the afore mentioned structures as input to lm. Thanks, John John Sorkin M.D., Ph.D. Chief, Biostatistics and Informatics Baltimore VA Medical Center GRECC, University of Maryland School of Medicine Claude D.

David, Again you have my thanks!. You are correct. What I want is not technically a contrast. What I want is the estimate for "regional" and its SE. I don't mind if I get these on the log scale; I can get the anti-log. Can you suggest how I can get the point estimate and its SE for "regional"? The predict function will give the point estimate, but not (to my knowledge)

Fellow Rers, Please forgive me if I have posted this to the wrong R list serve. Over the course of the years that I have used R and participated in this list server, I have noted a large number of questions and answers that direct people to specific packages. The multitude of packages is one of the great strengths of R. Unfortunately there is no (or at least I am not aware of) any single source

I have written an R function that produces multiple graphs. I use par(ask=TRUE) to allow for the inspection of each graph before the next graph is drawn. I am looking for a way to recall all graphs drawn in an R session, and a method that can be used to print all the graphs at one time. I know that I could simply print each graph after I inspect the graph, but this gets tiresome if one's

R 2.1.1 Win 2k Would someone suggest a method (or methods) that can be used to determine ntile cutpoints of a vector, i.e. to determine values that can be used to divide a vector into thirds such as 0-33 centile, 34-66 centile, 67-100 centile. If for example I had a vector: 1,2,3,4,5,6,7,8,9 and wanted to divide the vector into thirds I would have cut-points of 3, and 6. Thanks, John John

Widows XP R 2.3.1 I have been trying to make a data structure that will contain both the coefficients from a linear regression along with column and row titles AND the call, i.e. myreg<-lm(y~x+y+z) whatIwant<-cbind(c(summary(myreg)$call,"",""),summary(myreg)$coefficients) Neither the statement above, nor any one of twenty variations I have tried work. I would appreciate

Given a square matrix of variables X, is there any way to compute a multivariable correlation among all the variables in the array? It is possible to calculate the correlation of all pairs of variables in the array, but I want to know the correlation of all the variables taken together, i.e. for the matrix X=x1 x2 x3 x4 x5 x6 x7 x8 x9 I don't want the pair-wise correlations

I am using read.csv to read a CSV file (produced by saving an Excel file as a CSV file). The columns containing dates are being read as factors. Because of this, I can not compute follow-up time, i.e. Followup<-postDate-preDate. I would appreciate any suggestion that would help me read the dates as dates and thus allow me to calculate follow-up time. Thanks John John Sorkin M.D., Ph.D. Chief,

At the suggestion of many people, I have installed emacs on my linux (Fedora 8.0) computer with the intention of using emacs as window interface to R (2.6.0). I have gone though the emacs tutorial and don't see any information about how I should use emacs to run R. Can anyone suggest a document that I might read? In the past I have used R on a Windows XP system and used the built-in windowing

I want to place four plots on a page, and I would like to have all four plots share a common title. I have tried the following code, but the title is centered over the fourth graph and not centered across all four plots. Does anyone have any suggestions? R 2.1.1 windows xp oldpar<-par(mfcol =c(1,4),ask=TRUE) plot(p,varp) plot(p,SEp) plot(p,CVp) plot(p,ppval) title(paste("P and 95%CI