search for: 2.35

I am bewildered by the behaviour of tickmarks as demonstrated by the following code. (What I'm trying to do is draw a single tick mark extending from the axis all the way down to the tick label, which is two lines from the axis to make sure it doesn't overlap with the ``ordinary'' tick labels.) # Try 1: # Gap between tickmark and label. plot(1:10) axis(side = 1, at = 2.35,

Both of the approx functions work correctly individually, but they are not being distinguished in the for loop by the if statments. Any help would be appreciated. for loop of interest is below x <- (structure(list(Site = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,

Hello, My boss wants me to do a Duncan's test, which is under the agricolae package. Unfortunately I am not versed enough in R to run my data. I have 7 subspecies of deer mouse for which I have 23 measurements which are my variables of interest. I have run an ANOVA for each of the set of subspecies and variables, my data look like this: subspecies WMF 1 rowleyi 2.50 2 rowleyi 2.30

Perhaps there is an obvious answer to this, but I can't seem to figure it out. I want to generate a sequence of plots, where a variable (say x) is changed from plot to plot. For each plot I'd like to have a title indicating the value of x. However, what I really want is to use expression to typeset some math. A simple example is I'd like to do something like expression(mu==x), where

Hi Rusers, I found sometimes that the same values cannot be judged to be the same in R. Anybody knows the probelm? I think i ignored some minor detail. Thanks. Here is the example. ############ data1<-matrix(data=c(1,1.2,1.3,"3/23/2004",1,1.5,2.3,"3/22/2004",2,0.2,3.3,"4/23/2004",3,1.5,1.3,"5/22/2004"),nrow=4,ncol=4,byrow=TRUE)

I have written a wrapper for heatmap.2 called heatmap.w.row.and.col.clust which auto-generates breaks using breaks<-round((c(seq(from=(-20 * stddev), to=(20 * stddev))))/20, digits = 2) #(stddev in this case = 2.5) This has always worked well in the past but now I am getting an error that non-finite breaks are being generated. Drilling down, it seems that my wrapper is generating finite

Hi all, I am new user in R, I am trying to to use paste function to concatenate strings which has been fetched from database table(postgres database), the following are my code: when i do: > sqlFetch(channel,'transactions') outputs are following(only parts, there are around 200 transactions in total) orderid productname price quantity discount 1 T10248 potato 1.80

Hi there, is this a problem with the Wiki software or the DB? The delay is still tolerable, but not exactly nice to work with. http://www.voip-info.org/tiki-index.php?page=Asterisk+billing Page generated in: 2.35 seconds Philipp

I'm attempting to install RequestTracker on CentOS 6.5. Running "make testdeps" as recommended by RT's installation guide, I'm presented with lists of missing Perl modules. One of these lines reads: Encode >= 2.39 ...MISSING Now, "yum whatprovides '*/Encode.pm' " informs me that that module is part of the core Perl distribution, and is

Hi there, data1<-matrix(data=c(1,1.2,1.3,"3/23/2004",1,1.5,2.3,"3/22/2004",2,0.2,3.3,"4/23/2004",3,1.5,1.3,"5/22/2004"),nrow=4,ncol=4,byrow=TRUE) data1<-data.frame(data1) names(data1)<-c("areaid","x","y","date") data1 areaid x y date 1 1 1.2 1.3 3/23/2004 2 1 1.5 2.3 3/22/2004 3 2

Hello list, how could this happen? The Server doesn't respond from time to time with a high load avarage. We found a suspicious smbd process: top - 13:43:07 up 1 day, 2:27, 5 users, load average: 32.49, 58.41, 37.95 Tasks: 1196 total, 5 running, 1190 sleeping, 0 stopped, 1 zombie Cpu0 : 14.7% us, 3.8% sy, 0.0% ni, 79.8% id, 1.3% wa, 0.0% hi, 0.3% si Cpu1 : 1.3% us, 84.6%

Dear All. I have some problem with combined two data frame. .... I have first data frame .. GPAX THAI MATH SCINCE SOCIAL HEALT ART CAREER LANGUAGE 1227 2.99 3.32 2.50 2.64 3.05 3.60 3.72 3.57 2.62 1704 2.81 2.56 2.48 2.86 3.22 3.19 3.55 3.20 2.51 617 2.18 1.90 1.97 2.06 2.38 3.50 3.54 2.33 1.70 876 2.82 3.14 2.73 2.46 2.71 3.11 3.04 3.24 2.90

Dear R-list, I'm not sure what I've found about a function in DAAG package is a bug. When I was using cv.lm(DAAG) , I found there might be something wrong with it. The problem is that we can't use it to deal with a linear model with more than one predictor variable. But the usage documentation hasn't informed us about this. The code illustrates my discovery: > library(DAAG)

Hi all, I am facing difficulty on how to use bootstrap sampling and below is my example of function. Read a data , use some functions and use iteration to find the solution( ie, convergence is reached). I want to use bootstrap approach to do it several times (200 or 300 times) this whole process and see the distribution of parameter of interest. Below is a small example that resembles my

Dear All, I have just estimated this model: ----------------------------------------------------------- Logistic Regression Model lrm(formula = Y ~ X16, x = T, y = T) Model Likelihood Discrimination Rank Discrim. Ratio Test Indexes Indexes Obs 82 LR chi2 5.58 R2 0.088 C 0.607 0

Dear All, since some days I try to use the versions 2.35-4 of the survival package instead of versions 2.31, I had installed until now. Several changes in print.survfit, plot.survfit and seemingly in the structure of ratetabels effect some of my syntax files. Is there somewhere a documentation of these changes, besides the code itself? Thanks in advance, Heinz

I am a new user of R. I am trying to fit gam model with our air pollution data. I used Foreign package to call data from SPSS and used MGCV package to fit gam. The following are the steps I used: > dust<- read.spss("a:dust9600jan.sav") > c<-gam(MRESPALL~s(DUSTM)+s(TEMP)+s(RH),family=poisson,data=dust) > summary(c) Family: poisson Link function: log Formula: MRESPALL ~

Dear List, I have two questions about how to do predictions using lrm, specifically how to predict the ordinal response for each observation *individually*. I'm very new to cumulative odds models, so my apologies if my questions are too basic. I have a dataset with 4000 observations. Each observation consists of an ordinal outcome y (i.e., rating of a stimulus with four possible

Hi, When i tried to merge two datasets (multiple to multiple merge), i met a problem on how to stop a possible loop in the sampling arguments. ###My codes are as follows.### data1<-matrix(data=c(1,1.2,1.3,"3/23/2004",1,1.5,2.3,"3/22/2004",2,0.2,3.3,"4/23/2004",3,1.5,1.3,"5/22/2004"),nrow=4,ncol=4,byrow=TRUE)

Hello everybody, I have a problem with the model.table of anova. I have data (datos2) with 4 cluster (V7), calculated with daisy and hclust. str(datos2) 'data.frame': 56 obs. of 7 variables: $ Estacion: Factor w/ 56 levels "Abradelo","AltoDoRodicio",..: 1 2 3 4 5 6 7 8 9 10 ... $ Invierno: num 36 53.9 37.1 63.6 12.5 ... $ X : int 643449 616292 562796