search for: onsets

Hi, How can I get the '2+' into superscript in the following title: '[Ca2+]i onsets' I tried the command below, but it doesn't work. What am I missing? hist(X, main=expression(([Ca*]i^2+) 'onsets'), xlab = 'sec') -- View this message in context: http://r.789695.n4.nabble.com/superscript-characters-in-title-with-tp3006981p3006981.html Sent from the...

Happy New Year, r-helpers! I am using lowess to smooth a scatter plot, xx<-lowess(xinput,f=.04) #defaults for other args followed by turnpoints(xx$y) #defaults for other args I plot the smoothed result as well as turnpoints (using yy$tppos) on top of raw data plot. Result is exactly as expected, graphically. For another purpose, I calcuate the difference between turnpoints (representing

In increasing the computation time and bit rate with VBR: Has anyone considered implementing the standard audiological recognition technique of using the duration of zero energy (voice onset timing) to identify the presence of voiceless sounds? I would like a means of determining whether or not a given window will be full of voiced speech or not. Matt -- The swallow may fly south with the sun

Danardono <daodao99 at student.umu.se> wrote: > > While waiting for 2.1, for those who need function[s] for this > survival-splitting business, as I do, this 'survcut' function below > might be helpful. > It is not an elegant nor efficient function but it works, at least for > some examples below. > Ditto the following, for the case where there are multiple

I have three time series, x, y, and z, and I want to analyse the relations between them. However, they have vastly different resolutions. I am writing to ask for advice on how to handle this situation in R. x is a stimulus, and y and z are responses. x is a rectangular pulse 4 sec long. Its onset and offset are known with sub-millisecond precision. The onset varies irregularly -- it doesn't

I'm trying to get HOBOware Pro (http://www.onsetcomp.com/products/software/), a tool that interfaces with a USB based datalogger, to work under Wine. I have installed it, and it fails with the message: Code: Error occurred during initialization of VM Could not reserve enough space for object heap This seems to be fairly common among Java apps, and the solution appears to be setting -Xms

How can I change the position of the ylab, after enlarging the margins with par(mar=...)? Here is the relevant code snippet ---- par(mar=c(5.1,5.1,4.1,2.1)) plot(c(1979,2003),c(40,50),ylim=c(1,73),lab=c(20,10,1),pch=21,col='blue',bg='blue',axes=FALSE,xlab="Years",ylab="Onset/Withdrawl Date",font.lab=2) box() axis(1,las=2)

I would be grateful for advice about the following problem. It's not directly R-related, but I'm hoping that R will help me analyse the following data. I have a table which indicates the progression of a certain age-related disease. At a certain point in time, a population was sampled; and I have measurements for the age of each individual, and their disease stage. (Disease stage is an

I am writing to get a better handle on a warning I am getting from a coxph analysis I am doing. I am analysing age of onset of dementia *after* the onset of parkinson disease. My data looks like: age.park age.dem age.death censor x1 x2 x3 x4 1 76 87 88 0 16 33 E3 E3 2 75 84 84 0 33 36 E3 E3 3 77 81 81 1 NA NA

Colleagues, (R 2.10 on all platforms) I have a lengthy script (18000 lines) that runs within a graphical interface. The script consists of 100's of function followed by a single command that calls these functions (execution depends on a number of environment variables passed to the script). As a result, nothing is executed until the final line of code is read. It takes 15-20

Hola a todos, -Estoy estudiando el efecto de dos genotipos (~tratamientos) en la aparición de síndrome metabólico (MetS) con datos longitudinales recogidos a tiempo 0,7,10,15,20 y 25 años. -He hecho un dataframe con las siguientes variables MetS: Síndrome Metabólico (Si=1,No=0) bmi: Indice de masa corporal (IMC) cuando se produce la conversión a MetS+ . Para los que permancen MetS-, esta variable

Dear All, Writing sooner than I thought I'd need to. I'm using R 2.4 on Mac OS X, with RODBC, PostgreSQL 8.1 and Actual's ODBC driver. I have all my data in Filemaker 8.5, but it is automatically exported into PostgreSQL for analysis as Filemaker's ODBC and JDBC access is awful, slow and has a tendency to crash. I have disability data where for each patient there is a survival

On Fri, Nov 14, 2008 at 5:11 AM, Hans J. Koch <hjk at linutronix.de> wrote: >> I don't think anything currently in Ogg can do this. The closest I can >> think of is CMML's clip concept, but you'd still have to parse the entire >> stream to find them all. > > That's nearly useless for DVD-like applications. I don't know. Wouldn't it work if

Hi guys, just wanted to ask, on the onset of our page, we generate several div''s. What we noticed on an intermittent connection is that several divs don''t get to generate all the div''s sometimes so we had to reload our page. Would you have any technique on how we can do this? thanks bing -- Posted via http://www.ruby-forum.com/.

hello R-world, according to the strucchange package .pdf, "all procedures in this package are concerned with testing or assessing deviations from stability in the classical linear regression model." i'd like to test/assess deviations from stability in the Poisson model. is there a way to modify the strucchange package to suit my purposes, or should i use be using another

Hi I am sure that this question has been asked before ... appologies in advance This - which comes out very nicely - better than the commercial stuff. plotmeans (cdpy~Dodefordpy, Data = Dataset, connect = False, minbar = 1, mean.labels = FALSE, col = "blue", barwidth = 1.5, barcol = "red", ci.label = FALSE, xlab="Onset", pch = 15, par(las =2)). Only one snag I

Dear all, I'm having difficulty getting access to data generated by survfit and print.survfit when they are using with a Cox model (survfit.coxph). I would like to programmatically access the median survival time for each strata together with the 95% confidence interval. I can get it on screen, but can't get to it algorithmically. I found myself examining the source of print.survfit to

Jean-Marc Valin wrote: > The noise suppressor will only attempt to remove stationary noise, > such as thermal noise, fans, ... The AGC can indeed do strange > things in these cases, but it's been improved in svn (compared to > 1.2beta1). OK, then the problem is that I misunderstood the feature. I assumed that dynamic squelch was part of it, but it's really something more

I am following a document teaching how to use regression and right at the onset I get an R error. I understand that variables "conc" and "signal" should have the same length but I am using the what R manual suggests to drop the error and it is not cooperating. What gives? The manual says that the default is na.ombit by the way, not that it's addition does anything How

Another request for help implementing the 'apply' functions to avoid a loop structure... I am working with a data set that includes lab measurements taken at different dates for the subjects, with some subjects having more results than others. I would like to average lab results for each subject that were taken on the same day. I can do this using a for loop, but would like to know how