similar to: weighed mean of a data frame row-by-row

Is there a function/package that performs weighted 2D density estimates? I haven't found anything searching with those keywords, but perhaps there is a more general algorithm that I should be looking for. Any hints appreciated. Thanks, Hadley

Hello all, It seems that the GeneMeta passage returns NA in the respective row if any gene in the data sets to be synthesised are missing. Do you know of a way to overcome this problem? I tried using the 'impute' package to fill-in the missing values, but R crashes if 'impute' and 'GeneMeta' packages are used together. I have asked a separate question for that. Thanks

You are correct that the survreg routine only supports 'rho' of the Fleming-Harrington G-rho tests. This is a function of age -- I wrote the original code back when I was working with Tom (Fleming), and he was only using 1 parameter. Later he and David expanded the test to two parameters. This might be only the second request for the feature in the 30+ years since that date. Terry

Thank you Terry. Right now I can use comp() from survMisc package to do the 2-parameter version of F-H weighting. I think both SAS and stata offer the 2-parameter version, so just?thought it would be nice if survdiff() can have that option given it's standard package in R.? Thanks! John On Friday, February 16, 2018, 7:08:46 AM PST, Therneau, Terry M., Ph.D. <therneau at mayo.edu>

I would like to de-mean the 'vector' column of the following dataframe by factor: set.seed(5444) vector <- rnorm(1:10) factor <- rep(1:2,5) test.df <- data.frame(factor, vector) which is: factor vector 1 1 -0.4963935 2 2 -2.0768182 3 1 -1.5822224 4 2 0.8025474 5 1 0.3504199 6 2 0.2358464 7 1 -0.3989443 8 2 -0.3692544 9

> You could also try adding "-x usb_set_altinterface" to the command line > (or adding it to ups.conf). The lsusb output implies that the only valid > setting is 0 (bAlternateSetting), but it might need to be set explicitly. I checked with -x usb_set_altinterface and it says nut_usb_set_altinterface: usb_set_altinterface() should not be necessary - please email the

Hi again, > On Sep 8, 2016, at 10:05 AM, Vassilis Virvilis <vasvir at iit.demokritos.gr> > wrote: >> Now that's a problem. I am not sure that I can find >> >> 1) the original software >> 2) a (physical) windows machine in the vicinity of the UPS >> Ha! I jumped several hooks but I think I got it. 01. I contacted the store that sold us the UPS and

Thanks for the reply Bill. I am aware of the interrupts problem. To solve it I have already disabled my serial ports freeing up interrupts 3 and 4 and these are allocated to the two cards. This was done 2 months ago and has not solved the problem. Is there any way that something can wake up every now and then and generate these two interrupts? My current /proc/interrupts is as follows:

Hello everybody, I am trying to setup asterisk to redirect international calls via a carrier which uses a fixed price tel number. The scenario is Dial 087..something (UK number) Pause for answer at the other end Send required telephone number 003..etc followed by # What is the easiest way of doing this? I have trouble with both the pause and adding the # at the end of the number. Best

Well, the title says all for this one. It seems to crash the R-console, so it happens whether I use the R-gui or R-console directly or Emacs with ESS. I have R 2.9.0 on Windows Vista. Thanks, Vassilis

Dear R-List, I am sure there must be a very simple way to do this - I just do not know how... This is what I want to do: #my dataframe df<-data.frame(id=c("x01","x02","x03","x04","x05","x06"),a=c(1,2,NA,4,5,6),b=c(2,4,6,8,10,NA),c=c(NA,3,9,12,NA,NA),sum=c(3,9,15,24,15,6))    id    a     b     c   sum 1 x01  1     2    NA   3 2

A little deciphering > Looks like the ups always replies > 22 = 16035500 50005300 20004e00 6f002000 41006300 6b00 That is length = 0x16 = 22 type = 0x3 = string Message = "UPS No Ack" Very fun... Regards Vassilis Virvilis

I have an asterisk server running on Redhat 8.0 with a Digium TDM400P w/4 FXO modules (TDM04P) There are 2 lines going into the Digium card. One line is a Vonage digital line, and the other line is a Comcast voice line. I have a SIP Grandstream 100 phone connected to the Asterisk server. I also have IAX configured with FWD. The problem is that on occasionally, after talking for about 20

Halo, I don't know if this is already done but the following two patches (one for klibc) and a big one (several smaller incorporated to one) to modules-init-tools enables running modprobe and friends in early user space. There are some issues so I post here for discussion The porting strategy was copied from the udev package. I make a file mod_libc_wrapper.{c,h} in order to provide the

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Is is possible to specify multiple maildir location in mail_location? (default_mail_env in my case since I'm using version 1.0.rc15/debian etch). What I want to achieve is receive mail in /var/spool/mail, which is going to contain 1 Maildir per user, and have /home/%u/Maildir/ to store (move) messages from spool location. Postfix is taking care

I have to remove missing data both in character and numeric datatype.I tried using NA condition but it is not working ,please help me to solve this. -- View this message in context: http://www.nabble.com/Handling-missing-data-tp25530192p25530192.html Sent from the R help mailing list archive at Nabble.com.

Hello! I am doing Principle Componenets Analysis using "psych" package: mypc<-principal(mydata,5,scores=TRUE) However, I was asked to run a case-weighted PCA - using an individual weight for each case. I could use "corr" from "boot" package to calculate the case-weighed intercorrelation matrix. But if I use the intercorrelation matrix as input (instead of the

Hello, I am wondering if there is an easy way to combine loess() with glm() to produce a locally fitted generalised regression. I have a data set of about 5,000 observations and 5 explanatory variables, with a binary outcome. One of the explanatory variables (lets call it X) is much more predictive than the others. A single glm() regression over the entire data set produces rather poor results,

Dear R-experts: I am using survreg() to estimate the parameters of a Weibull density having right-censored observations. Some observations are weighted. To do that I regress the weighed observations against a column of ones. When I enter the data as 37 weighted observations, the parameter estimates are exactly the same as when I enter the data as the corresponding 70 unweighted observations.

Hello all R users I want to calculate this univariate integral: exp(-x)*sum(y^x) respect to x from 0 to 3 where y is a vector y=(2,3,5). In fact, the original y vector has a large number of elements but I propose with 3 elements. I know that I can resolve this problem doing fun <- function(x) exp(-x)*(2^x+3^x+5^x) integrate(fun,0,3) When the y vector has a large number of elements the