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Hi All: Greetings, and best wishes from the festive times here at Kolkata, India -- the time of Durga Puja celebrations. I seek your advice as I try plotting lines for my data. The problem: I have created a dataframe that looks like this (name: myFrame): lowest second third fourth highest significance INAS 0.107 0.115 0.123 0.115 0.166 0.000 MMA 0.091 0.107 0.115

  Dear R helpers   Suppose I have two sets of ranges (interest rates) as   Range 1 : (7 – 7.50, 7.50 – 8.50, 8.50 – 10.00) with respective probabilities 0.42, 0.22 and 0.36.     Range II : (11-12, 12-14, 14-21) with respective probabilities 0.14, 0.56 and 0.30 respectively.     My problem is to form the combinations of these ranges in a decreasing order of joint probabilities. It is assumed that

Hi: I need help with geom_text(). I would like to count the number of Locations and put the sum of it right above each bar. x <- "Location Lake_dens Fish Pred Lake1 1.132 1 0.115 Lake1 0.627 1 0.148 Lake1 1.324 1 0.104 Lake1 1.265 1 0.107 Lake2 1.074 0 0.096 Lake2 0.851 0 0.108 Lake2 1.098 0 0.095 Lake2 0.418 0 0.135 Lake2 1.256 1 0.088 Lake2 0.554 1 0.126 Lake2 1.247 1 0.088

Hi, I'm reading part of a table from postgres, so I'm getting a data frame. how can I extract the numerica values so I can operate on them. > res <- dbGetResult(mydata) > str(res) `data.frame': 5 obs. of 8 variables: $ cyx.1: num 0.149 -0.278 0.114 0.060 0.109 $ cyx.2: num 0.158 -0.070 0.063 0.149 0.150 $ cyx.3: num 0.052 -0.350 0.114 0.126 0.238

Hej! I have the following problem: I would like to do partial correlations on non-parametric data. I checked "pcor" (Computes the partial correlation between two variables given a set of other variables) but I do not know how to change to a Spearman Rank Correlation method [pcor(c("BCDNA","ImProd","A365"),var(PCor))] Here''s a glimpse of

Dear R-Helpers, I've looked high and low for a function that provides frequencies, proportions and cumulative proportions side-by-side. Below is the table I need. Is there a function that already does it? Thanks, Bob > # Generate some test scores > myValues <- c(70:95) > Score <- ( sample( myValues, size=1000, replace=TRUE) ) > head(Score) [1] 77 71 81 88 83 93 > >

OS X R 4.3.3 Colleagues I have created objects using the Surv function in the survival package: > FIT.1 Call: survfit(formula = FORMULA1) n events median 0.95LCL 0.95UCL SUBDATA$ARM=1, SUBDATA[, EXP.STRAT]=0 18 13 345 156 NA SUBDATA$ARM=2, SUBDATA[, EXP.STRAT]=1 13 5 NA 186 NA SUBDATA$ARM=2, SUBDATA[, EXP.STRAT]=2 5

Dear all, I would like to know if there is a function for sorting a data.frame based on one column. sort() does it for a single vector but not for the whole data. order() does it if there are relations between the columns but in my case it is simply a data.frame. Further, I would like to plot other data, pop.size<- c(800, 800, 1500, 1000, 158, 300, 740, 250, 2000, 1500, 250, 700)

Hi r-users,   I would like to extract the data that match.  Attached is my data: I'm interested in matchind the value in column 'intg' with value in column 'rand_no' > cbind(z=z,intg=dd,rand_no = rr)             z  intg rand_no    [1,]  0.00 0.000   0.001    [2,]  0.01 0.000   0.002    [3,]  0.02 0.000   0.002    [4,]  0.03 0.000   0.003    [5,]  0.04 0.000   0.003    [6,] 

Hi all, I'm trying to figure out the example about mixed models in the Pinheiro and Bates book (Mixed-Effects Models in S and S-Plus, 2000, pp. 135-137). One thing I don't understand is: When I run the command fm1Orth.lm <- lm( distance ~ age, Orthodont ) followed by fm2Orth.lm <- update( fm1Orth.lm, formula = distance ~ Sex*age ) and then do summary(fm2Orth.lm)

the study design of the data I have to analyse is simple. There is 1 control group (CTRL) and 2 different treatment groups (TREAT_1 and TREAT_2). The data also includes 2 covariates COV1 and COV2. I have been asked to check if there is a linear or quadratic treatment effect in the data. I created a dummy data set to explain my situation: df1 <- data.frame( Observation =

Short:     Which package do I need to install to get "auto/I18N/Langinfo/autosplit.ix"? Long: The problem I have was discussed almost a year ago (see this thread), but the resolution was not complete... I''m using Mark Johnson''s slim.py script (package list below), against repo=http://pkg.opensolaris.org/dev, followed by `pkg install xvm-gui` and `svcadm enable

On Mon, 2007-05-14 at 23:41 +0200, vax9000 at gmail.com wrote: > Full_Name: vax, 9000 > Version: 2.4.0, 2.2.1 > OS: 2.4.0: Mac OS X; 2.2.1: Linux > Submission from: (NULL) (192.35.79.70) > > > To reproduce this bug, first go to the website "http://llmpp.nih.gov/DLBCL/" and > download the 14.8M data set "Web Figure 1 Data file". The direct link is >

Dear all, It was a pleasure to meet you at Iowa State University. Two days ago I submitted two experimental packages to CRAN (hope it will be there soon): rindex: quick indexing of large objects (currently only character, see ?index) regtest: some first support for automated regression testing (heavily used in \dontshow{} section of ?index) With rindex you can for example i <-

Given an x-vector with, say, 3 elements, I would like to compute the following vector of permutated products (1-x1)*(1-x2)*(1-x3) (1-x1)*(1-x2)*x3 (1-x1)*x2*(1-x3) x1*(1-x2)*(1-x3) (1-x1)*x2*x3 x1*(1-x2)*x3 x1*x2*(1-x3) x1*x2*x3 Now, I already have the correctly sorted matrix of permutations! So, the input looks something like: #input x<-c(0.3,0.1,0.2) Nx<-length(x) Ncomb<-2^Nx

LANG=C DRI_PRIME=1 vainfo libva info: VA-API version 0.40.0 libva info: va_getDriverName() returns 0 libva info: Trying to open /usr/X11R7/lib/dri/nouveau_drv_video.so libva info: Found init function __vaDriverInit_0_40 libva info: va_openDriver() returns 0 vainfo: VA-API version: 0.40 (libva ) vainfo: Driver version: Mesa Gallium driver 20.3.0-devel for NVA3 vainfo: Supported profile and

Hi Dennis, look at the help page for summary.survfit, the Value n.event. G?ran On 2024-05-15 22:41, Dennis Fisher wrote: > OS X > R 4.3.3 > > Colleagues > > I have created objects using the Surv function in the survival package: >> FIT.1 > Call: survfit(formula = FORMULA1) > > n events median 0.95LCL 0.95UCL >

I currently work on a draft of an aquatic bioassessment. The conditions tested are the following: ER river water T dechlorinated water control 0.5 + 0.5mg / L of malate T + 1 dechlorinated water control + 1g / L of malate T ED dechlorinated water control SED + ER + river water sediment SED ED + sediment + water dechlorinated. It is the result of AChE in muscle (fillet of fish). The production of

Dear R-ophiles, I've found something very odd when I apply convolve to ever larger vectors. Here is an example below with vectors ranging from 2^11 to 2^17. There is a funny bump up at 2^12. Then it gets very slow at 2^16. > for( i in 11:20 )print( system.time(convolve(1:2^i,1:2^i,type="o"))) user system elapsed 0.002 0.000 0.002 user system elapsed 0.373

Dear R gurus I am running a GLMM that looks at whether chimpanzees spend time in shade more than sun (response variable 'y': used cbind() on counts in the sun and shade) based on the time of day (Time) and the availability of shade (Tertile). I've included some random factors too which are the chimpanzee in question (Individual) and where they are in a given area (Zone). There are