search for: characteristically

Hi, I have a rather complex xml document that I am attempting to parse based on attributes: <Manifest xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"> <!-- eName : name of the element. eValue : value of the element. --> <OutputFilePath>D:\CN_data\Agilent\Results\</OutputFilePath> <FilesList> <File>

I'm working on adding data detection to llvm-objdump, so it prints out raw data for symbols with type SymbolRef::ST_Data instead of disassembling them. This causes llvm/test/MC/ARM/Windows/mov32t-range.s to fail, because the symbol "truncation" comes back as SymbolRef::ST_Data, and the code gets dumped as bytes instead of disassembled. I traced the problem back to

The section is .text, so I assume it’s got IMAGE_SCM_CNT_CODE set. The problem is the symbol is marked (read & execute), but the test is (read & !write), so the symbol gets marked as ST_Data instead of ST_Other. From: David Majnemer [mailto:david.majnemer at gmail.com] Sent: Friday, August 22, 2014 5:44 PM To: Ted Woodward Cc: LLVM Developers Mailing List Subject: Re: [LLVMdev]

I have a data set which I would like to plot as a set of concentric circles. The data represent a count of the number of characteristics shared by various elements - an example would look like this: 1 100 2 75 3 50 4 25 I.e. all four sets share 25 characteristics, three of them share 50 characteristics, and so on. I would like to plot these as concentric circles, with the circle size

Hi, I wish to calculate the characteristic path length of a graph. Is average.path.length(g) in 'igraph' the same as calculating the characteristic path length of the graph? Thanks, Kumar -- View this message in context: http://r.789695.n4.nabble.com/Characteristic-Path-length-calculation-tp3398048p3398048.html Sent from the R help mailing list archive at Nabble.com.

Dear R-helpers: I want to calculate area under a Receiver Operator Characteristic curve. Where can I find related functions? Thank you in advance Xiao

The characteristic function is the inverse Fourier transform of the distribution function. The characteristic function of a normaly distributed random variable is exp(-t^2/2). x=seq(-2,2,length=100) fft(pnorm(x),inverse=T)/length(x) exp(-x^2/2) Why aren't the inverse fft and the mentioned function the same? Thanks for help, Thomas

hey, I was wondering - is there an option to rsync which allows you to exclude transfers of files with a certain size or other characteristics? I want to setup a 'partial' rsync mirror where I only pull files under 5M, for example.. I see the option for including/excluding file names in the usage, but not file sizes.. Ed

Dear R users, I 'm working on a dataset consisting of 4 different dataframes with tree, leaf, fruit and seed measurements made on 300 trees, coming from 10 provenances (30 trees per provenance, 10 leaves/fruits/seeds per tree). Provenances are fixed effects (they were not randomly chosen), but trees within provenances and leaves/fruits/seeds within trees were randomly assigned. I wanted to

Hi, Being in the process of translating some of my SAS programs to R, I encountered one difficulty. I have a solution, but it is not elegant (and not pleasant to implement). I have a large dataset with many variables needed to identify the origin of a sample, many to describe sample characteristics, others to describe site characteristics. I want only a (shorter) list of sites and their

Hello all! I've posted the question before but I am still struggling for an answer, please help if you can;-) Suppose a discrete series of data is generated by the following equation: CF=exp(-(t^2)/2) which is the characteristic function of a random variable X with standard normal distribution, how do I *numerically* solve for its probability density function? i.e., obtain a series of data

I have a data set with many missing observations. When I run a regression, R of course discards the observations (the whole row) that have "NA". I want to tabulate some baseline characteristics (column means) but only for the observations that R used for the regression. I tried to recreate this data frame by using na.omit on the original data frame, but this will not work as this will

I'm reading about Local channel and applications. One fancy idea came up: if my generic dial plan uses Dial() with no timeout, can I assign it a timeout for special purposes by Dial(Local/some-exten@mycontext,,20) or even add other Dial() options. Well, I can't. (Maybe a feature request?) So this pseudo channel seems to lack some characteristics of a "real" one. Now the

Hello R people, I have a data file with 101 numeric variables: one variable called IDN (the individual's unique id number, which I need to retain, and which ranges from 1000 to 1320; some numbers are obviously skipped), and V1 to V100 (each has a value of 0 or 1; these 100 variables represent sequentially ordered days and whether a characteristic was present or absent--e.g., v1 is day 1 and a

Hi, I have a local development environment and remote production environment, however I am really just learning/playing, hence I would like to be able to define these environments separately in the config files, however.... I would like my production environment to really act in a development mode fashion at the moment (i.e. sense updates I make without any need to restart things etc). Is

I am indebted to Deepayan Sarkar for lattice graphics, Fritz Leisch for Sweave and the authors of the beamer package for LaTeX. For me these are a "killer app" combination. I wouldn't want to go back to creating presentations in any other way. When I create a presentation I use a Makefile that allows me to the presentation version of the slides, a 4-up version for printing on

Hi all, I am working with some social network analysis in R and ran into a problem I just cannot solve. Each observation in my data consists of a respondent, some characteristics and up to five friends. The problem is that all of these five friends might no show up later as a respondent (observation). Therefore I might not have characteristics on all the friends listed in the data and I want to

I'm trying to do a sort of home-brew item-characteristic-curve. This is a plot of the probability of getting a test item correct, as a function of the mean score on the test. (The last part is the home brew part.) Logistic regression with glm would work nicely, EXCEPT for the fact that the curve requires a guessing parameter. So the asymptote on the left is not 0 but rather something like

Dear User R It's been a pleasure talking with you. I am newcomer use R. Would you please help me how to translate the script below to "R" script? * Area under receiver operating characteristic (AU-ROC) predict r1m1p, p roctab malaria r1m1p, graph summary * Area under receiver operating characteristic (AU-ROC) curve predict r1m2p, mu roctab malaria r1m2p, graph summary

*Dear Bert, * Thank you very much for your feedback and the useful link https://rseek.org/ and https://www.r-bloggers.com/calculating-auc-the-area-under-a-roc-curve/. Actually, I want to know different performance between Stata and R, in multilevel logistic regression. For this purposes, I replicate ".do" file use Stata in