similar to: Extracting the p of F statistics from lm

I am writing some code to obtain publication-like plots (like the ones can be obtained with SigmaPlot). I am not able to find the dimensions of a point. Parameters like cex make you able to make it bigger or smaller but I need to know the exact dimension (in relative coordinates : if my plot is 640x480 a dot plotted with cex=1.5 will be...) Massimo Cressoni

I am not able to compile R under ubuntu Edgy. ./configure error message is configure: error: --with-x=yes (default) and X11 headers/libs are not available I do not know which library is missing (I tried to install some X11 libs but were already on the system). Massimo Cressoni

I am trying to write a function that fits a sigmoid given a X and Y vector guessing the start parameters. I use nls. What I did (enclosed) seems to work well with many data points but if I want to fit small vectors like : pressure <- c(5,15,9,35,45) gas <- c(1000,2000,3000,4000,5000) it do not work. The help page says that it do no not work on zero residual data. Massimo Cressoni

I need to perform the Exact Wilcoxon Mann-Whitney on a subset of my database. Assuming that IPPO is my data frame and IPPOBIS is the subset my variable still have 3 different levels and the function wilcox_test (package "coin") does not accept it. I do not know how to overcome this problem. ippo <- c(rep("A",10),rep("B",10),rep("C",10)) ippo2 <-

I know that this maybe a trivial question. I am not able to plot pedices in graph axes. Instead I am able to plot different math symbols : XLABEL <- expression(paste(cmH,lim(f(x), x %->% 0),"O PEEP")) works well XLABEL <- expression(paste(cmH,[2],"O PEEP")) is considered a wrong expression. Thanks

I would really appreciate it if someone can give suggestions on how to do spectra fitting in R using ordinary least square fitting and non-negativity constraints. The lm() function works well for ordinary least square fitting, but how to specify non-negativity constraints? It wouldn't make sense if the fitting coefficients coming out as negative in absorption spectra deconvolution. Thanks.

Thanks. Eric Leifer, Ph.D. Office of Biostatistics Research National Heart, Lung, and Blood Institute 6701 Rockledge Drive, MSC 8217 Bethesda, MD 20892-8217 Email: LeiferE@NHLBI.NIH.GOV Phone: 301-435-0436 FAX: 301-480-1862

Hello everybody: I have just started using R, specifically the clustering packages. Despite the vastness of the functionality of the system, I have found it very flexible and intuitive. It has been great fun to experiment with it. Nevertheless, I am under tight time constraints to complete a cluster analysis of some data and need to come up with a "quick" solution for the following

Hi to all, I have Samba configured as domain member with winbind and kerberos, I can access all share but I have some problem with the home directories because it ask me for password. This is my smb.conf [global] workgroup = domain netbios name = Manufac server string = Server di rete comment = server di rete encrypt passwords = true realm =

Hi, the problem I am reporting relates to RH Linux 6.0 I have successfully mounted a disk from a windows NT server machine, using smbmount as follows: $ smbmount //machine/service -c 'mount /mnt/NTgroups -u local_owner' -U remote_username and everything looked fine. Now I have just noticed that when "touching" or creating files everything behaves strangely, that is the date is

Given this data frame (a simplified, essential reproducible example) A<-c(8,7,10,1,5) A_flag<-c(10,0,1,0,2) B<-c(5,6,2,1,0) B_flag<-c(12,9,0,5,0) mydf<-data.frame(A, A_flag, B, B_flag) # this is my initial df mydf I want to get to this final situation i<-which(mydf$A_flag==0) mydf$A[i]<-NA ii<-which(mydf$B_flag==0) mydf$B[ii]<-NA

Hi puppet masters, while working on my site I came across a requirement that might be helpful for others as well.... With the aim of confining human errors as much as possible, I thought that it would be nice to have yum repositories disabled so that specific repositories could be enabled for certain packages. This is easily implementable via command-line, but I found that the

Hello an update about my question: I worked out the following solution (with the package "dplyr") library(dplyr) mydf%>% mutate(speed_vehicles=n_vehicles*mydf$speed) %>% group_by(date_time,type) %>% summarise( sum_n_times_speed=sum(speed_vehicles), n_vehicles=sum(n_vehicles), vel=sum(speed_vehicles)/sum(n_vehicles) ) In fact I was hoping to manage everything in a

hi all I have this dataframe (created as a reproducible example) mydf<-structure(list(date_time = structure(c(1508238000, 1508238000, 1508238000, 1508238000, 1508238000, 1508238000, 1508238000), class = c("POSIXct", "POSIXt"), tzone = ""), direction = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L), .Label = c("A", "B"), class =

Hi to everybody, This my first post on the list. I''m a newby of mongrel & rails, I''ve deployed my first project and everything seems to work fine, the only problem I have is the following: After about 1 or 2 days of the mongrel_rails daemon running the mongrel.pid in the log directory disappears, the mongrel process is still there running but doesn''t respond

Hi I set up my ups with driver snmp-ups, and it get recognized as a AEC T2003. In the nut-cgi upstats page input/output/load are displayed corectly, but the Status field is marked as "Not supported". Is "Status" important to initiate shutdown in case of low battery ? Will my server shut down correctly ? thanks Massimo I include "upsc snmp@localhost" output:

yes, it works, even if I do not really get how and why it's working the combination of logical results (could you provide some insights for that?) moreover, and most of all, I was hoping for a compact solution because I need to deal with MANY columns (more than 40) in data frame with the same basic structure as the simplified example I posted thanks m ----- Messaggio originale ----- Da:

Hi, my application is written in std C++ and it makes a matrix multiplication: so it uses only CPU and memory (no i/o, no network). I''m quite surprise that with CAP = 100% I got my results in about 600 seconds and with CAP = 50% I got my results in about 1800 seconds (around 3 times longer). For this kind of application I was expecting to get results in about 1200 seconds (2 times

Hi R Users, I am going to run a multiple linear regression with around 57 independent variables. Each time I run the model with just 11 variables, the results are reasonable. With increasing the number of independent variables more than 11, the coefficients will get ?NA? in the output. Is there any limitation for the number of independent variables in multiple linear regressions in R? I attached

Dear Massimo, It seems straightforward to use weighted.mean() in a dplyr context library(dplyr) mydf %>% group_by(date_time, type) %>% summarise(vel = weighted.mean(speed, n_vehicles)) Best regards, ir. Thierry Onkelinx Statisticus / Statistician Vlaamse Overheid / Government of Flanders INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND FOREST Team