similar to: Pseudo R^2 for logit - really naive question

I have a contingency table with a 0/1 variable (fwr) that flags a particular condition, a weight variable (cnt) and other variables (e.g. zz) characterizing that observation of the table. I am trying to use GLM. By converting the variables to factors and running the following regression: fwr1<-factor(fwr) zz1<-factor(zz1) res1<-glm(fwr1 ~ zz1,weights=cnt) Is that appropriate? Paul M.

Hi everyone, Here's a question about extracting data from a dataframe: Let's say I've got a dataframe with two vectors, TEST and GENDER. GENDER contains a 1 for males and 2 for females. I want to separate the results of TEST by GENDER so I can compare their means. What's the most efficient way to do this with R? -Tim -- Tim Wilson | Visit Sibley online: | Check out:

I would like to impute missing data in a set of correlated variables (columns of a matrix). It looks like transcan() from Hmisc is roughly what I want. It says, "transcan automatically transforms continuous and categorical variables to have maximum correlation with the best linear combination of the other variables." And, "By default, transcan imputes NAs with "best

Dear R community. I´m working with a generalized linear model which the response variable is a categorical one and the predictive variables are weather conditions. I have 250 different places where I need to fit the model. In some of these places I have strong correlations between some of the variables so I need to deal with this problem. I found a work similar than mine where they use tha

Dear R users, I want to retrieve "..." argument values within a function. Here is a small exmaple: myfunc <- function(x, ...) { if (hasArg(ylim)) a <- ylim plot(x, ...) } x <- rnorm(100) myfunc(x, ylim=c(-0.5, 0.5)) Error in myfunc(x, ylim = c(-0.5, 0.5)) : Object "ylim" not found > I need to retrieve values of "ylim" (if it is defined

Dear all, I am using transcan to impute missing values (single imputation). I have several dichotomous variables in my dataset, but when I try to impute the missings sometimes values are imputed that were originally not in the dataset. So, a variable with 2 values (severe weight loss or no/limited weight loss) for example coded 0 and 1, shows 3 different values after imputation (0, 1 and 2). I

Hello: I have been trying to impute missing values of a data frame which has both numerical and categorical values using the function transcan() with little luck. Would you be able to give me a simple example where a data frame is fed to transcan and it spits out a new data frame with the NA values filled up? Or is there any other function that i could use? Thank you avneet ===== I believe in

Dear all; I am trying to use HMISC imputation function to perform multiple imputations on my data and I keep on getting errors for the code given in the help files. When using "aregImpute" the error is; >f <- aregImpute(~y + x1 + x2 + x3, n.impute=100) Loading required package: acepack Iteration:1 Error in .Fortran("wclosepw", as.double(w), as.double(x),

  I have timeseries data for some factors, and some missing values are there in those factors, I want impute those missing values without disturbing the distribution of that factor, and maintaining the correlation with other factors. Pl. suggest me some imputation methods. I tried some functions in R like aregImpute, transcan. After the imputation I am unable to retrive the data with imputed

Thank you for helping me! I try the "pretty" funtion to select the x-axis position value.Then I use the "format" funtion. xax.pos <- pretty(as.numeric(x$x.name)) format(xax.pos,'%d %b %y') > xax.pos [1] 1091600000 1091800000 1092000000 1092200000 1092400000 1092600000 1092800000 [8] 1093000000 There are something wrong. I found the xax.pos has been changed to

UPDATE: It turned out QEMU still dumped core with that patch applied. That said, I'm still interested to know how to report issues with QEMU from centos-virt repo. Thanks, Ray > -----Original Message----- > From: Xiong, Huan > Sent: 2018?6?22? 11:12 > To: 'centos-virt at centos.org' <centos-virt at centos.org> > Subject: Q: how can I request to add an upstream

I'm looking for a package that has a start-of-the-art method of imputation of missing values in a data frame with both continuous and factor columns. I've found transcan() in 'Hmisc', which appears to be possibly suited to my needs, but I haven't been able to figure out how to get a new data frame with the imputed values replaced (I don't have Herrell's book). Any

Dear R users, This is more a statistical question rather than an R question. I'd appreciate it if you can give me some suggestions. I have a sample of a time series (sample size 500, fat tail in density). I am trying to calculate the Standard error of standard deviation of a sub-block-sample (sample size 250). I take 100 this kind of sub-block-sample, randomly. For these 100 subsamples, I

Dear all, I try to fit least absolute deviation (LAD) regression with R. I couldn't find any command to carry out LAD. What I am doing now is using nlm() and setting the function argument to minimize the sum of the absolute deviation. But for some data it keeps giving out the error message: Error in nlm(absdev, b.start) : non-finite value supplied by nlm. (there is no na in my dataset.) I

Hi everybody, I have trouble installing my own package under R 2.1.0 (it is fine under R 2.0.1). My OS is Windows NT. I installed my package 'mag' by using menu "Packages/Install package from local zip files....". It's fine (html package description was updated). But when I typed in library(mag) it gave me error: Error in library(mag) : there is no package called

Has anyone programmed condition indexes in R? I know that there is a function for variance inflation factors available in the car package; however, Belsley (1991) Conditioning Diagnostics (Wiley) notes that there are several weaknesses of VIFs: e.g. 1) High VIFs are sufficient but not necessary conditions for collinearity 2) VIFs don't diagnose the number of collinearities and 3) No one has

Dear Users, I try to calculate condition indexes and variance decomposition proportions in order to test for collinearity using colldiag() in perturb package, I got a large index and two variables with large variance decomposition proportions,but one of them is constant item.I also checked the VIF for that variable, the value is small.The result is as follows: Index intercept V1

----- Original Message ----- > From: "Zhang Huan" <zhanghuan at open-fs.com> > To: "Raghavendra G" <raghavendra at gluster.com> > Cc: "GlusterFS Maintainers" <maintainers at gluster.org>, "Gluster Devel" <gluster-devel at gluster.org>, "Kaushal Madappa" > <kmadappa at redhat.com> > Sent: Tuesday, May 30,

Hello. I have an XYY series that I would like to graph with matplot() or some other single function that will do the trick. The X in question is a vector of POSIXt values obtained from strptime(). Is it possible to tell matplot() how to handle POSIXt x values? I have examined the examples at http://lark.cc.ukans.edu/~pauljohn/R/statsRus.html#5.22 , but would prefer not have to overlay the

Thanks Jim for looking into that, I was really starting to wonder what was going on. Let me know if you find a way to tell the compiler to stop complaining. Jean-Marc Jim Crichton a ?crit : > I looked back at my old C55 EC build, and I had the same warning in > mdf.c which Mike found. The assembly code did have a valid shift, and > this build did cancel echo. > > When I built