search for: maxbr

...00 a=fmtp:98 profile-level-id=428016;max-mbps=35000;max-fs=3600;max-smbps=323500 a=rtpmap:99 H263-1998/90000 a=fmtp:99 custom=1280,800,0;custom=1280,768,0;custom=1280,720,3;custom=1024,768,4;custom=1024,576,2;custom=800,600,3;cif4=2;custo a=rtpmap:34 H263/90000 a=fmtp:34 cif4=2;cif=1;qcif=1;sqcif=1;maxbr=19200 a=rtpmap:31 H261/90000 a=fmtp:31 cif=1;qcif=1;maxbr=19200 a=rtcp-fb:* nack pli a=sendrecv a=content:main a=label:11 a=answer:full m=application 5078 UDP/BFCP * c=IN IP4 192.168.50.10 a=floorctrl:c-s a=confid:1 a=floorid:2 mstrm:12 a=userid:1 a=setup:passive a=connection:new m=video 48264 RTP/...

Given this example mean.values<-colMeans(VADeaths) mean.values<-apply(VADeaths, 2, mean) median.values<-apply(VADeaths, 2, median) dotchart(VADeaths, gdata=mean.values) dotchart(VADeaths, gdata=median.values) is it possible to ?combine? a single dotchart showing both the mean and the median for each single group (with different plotting symbols)? ?is it that possible with the use of

...eb) about the comparison of ?wilcoxon mann whitney? u test outcomes from different stat packages: http://www.jstor.org/discover/10.2307/2685616?uid=3738296&uid=2129&uid=2&uid=70&uid=4&sid=47699045750617 Any of you have faced the same type of issues? Or am I completely wrong? maxbre -- View this message in context: http://r.789695.n4.nabble.com/Wilcoxon-Mann-Whitney-U-value-outcomes-from-different-stat-packages-tp4631703.html Sent from the R help mailing list archive at Nabble.com.

Given the following chart: i.e. a boxplot with a grid boxplot(x~y) grid(nx=NA,ny=NULL) my question: how to avoid the overlapping of boxes (and whiskers) by grid lines? thank you for any help pointing me in the right direction max -- View this message in context: http://r.789695.n4.nabble.com/how-to-avoid-grid-overlapping-in-a-boxplot-tp4495955p4495955.html Sent from the R help mailing list

...n not ?move? all commands inside the main plotting? xyplot() - without loosing some relevant features of the chart) any help much appreciated sorry for such trivial question but I?m using R since a very short time: please keep your replies as much simple and self explanatory as possible thank you maxbre -- View this message in context: http://r.789695.n4.nabble.com/lattice-panel-fine-control-tp3566347p3566347.html Sent from the R help mailing list archive at Nabble.com.

This is my reproducible example: example<-structure(list(SENSOR = structure(1:6, .Label = c("A", "B", "C", "D", "E", "F"), class = "factor"), VALUE = c(270, 292.5, 0, 45, 247.5, 315), DATE = structure(1:6, .Label = c(" 01/01/2010 1", " 01/01/2010 2", " 01/01/2010 3", " 01/01/2010

my reproducible example test<-structure(list(site = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L), .Label = c("A", "B", "C", "D", "E"), class = "factor"),

by considering this example from barley dataset #code start dotplot(variety ~ yield | site, data = barley, scales=list(x=list(log=TRUE)), layout = c(1,6), panel = function(...) { panel.dotplot(...) #median.values <- tapply(x, y, median) # medians for each variety #panel.abline(v=median.values, col.line="red") # but this

...- 9 2 IN IP4 172.16.148.129 s=CounterPath eyeBeam 1.5 c=IN IP4 172.16.148.129 t=0 0 m=audio 18342 RTP/AVP 18 3 0 101 a=fmtp:18 annexb=no a=fmtp:101 0-15 a=rtpmap:101 telephone-event/8000 a=sendrecv a=x-rtp-session-id:07F885091DAF4305868C0F432F6512CF m=video 35840 RTP/AVP 34 115 125 a=fmtp:34 QCIF=2 MAXBR=1960 a=fmtp:115 QCIF=2 MAXBR=1960 a=fmtp:125 profile-level-id=42e015; max-br=4000; max-mbps=19800 a=rtpmap:34 H263/90000 a=rtpmap:115 H263-1998/90000 a=rtpmap:125 H264/90000 a=sendrecv a=x-rtp-session-id:399907E52958448ABF8B7176DCD44BD5 <-------------> --- (11 headers 20 lines) --- Found RTP...

given this example library(corrgram) corrgram(mtcars[2:6], order=TRUE, upper.panel=panel.conf, lower.panel=panel.pie, diag.panel=panel.minmax, text.panel=panel.txt) how can I change the variable names in main diagonal? (so that I can put more informative names of variables) I think to understand that this should be done by modifing the panel.txt function but

hello all, this is my reproducible example data frame test<-structure(list(date = structure(c(1262300400, 1262304000, 1262304000, 1262307600, 1262307600, 1262311200, 1262311200, 1262314800, 1262314800, 1262318400, 1262318400, 1262322000, 1262322000, 1262325600, 1262325600, 1262329200, 1262329200, 1262332800, 1262332800, 1262336400, 1262336400, 1262340000, 1262340000, 1262343600,

Hi all, given this example #start a<-c(0,70,50,100,70,650,1300,6900,1780,4930,1120,700,190,940, 760,100,300,36270,5610,249680,1760,4040,164890,17230,75140,1870,22380,5890,2430) length(a) b<-c(0,0,10,30,50,440,1000,140,70,90,60,60,20,90,180,30,90, 3220,490,20790,290,740,5350,940,3910,0,640,850,260) length(b) out<-ks.test(log10(a+1),log10(b+1)) # max distance D

After a long and winding road (sorry but I'm a novice) I get to a final result which is quite close to what I need; nevertheless I would like to tweak a little further the xyplot so that I can get ***for each single panel defined by variable z*** a finer control over: -the x and y the limits: I would like to be the same for both axes; -the number of thick marks: again I would like to be same

I want to get access to the code of an S4 method in order to possibly modify a function to accomplish my particular needs: in my case the function in is cenfit() from the package NADA Now, given my reproducible example: my.ex<-structure(list(TEC = c(0.21, 0.077, 0.06, 0.033, 0.014, 0.0072), LR = c(0L, 0L, 1L, 0L, 1L, 0L)), .Names = c("TEC", "LR"), class =

Given my reproducible example test<-structure(list(site = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L), .Label = c("A", "B", "C", "D", "E"), class =

I am trying to create a frequency distribution and I am a bit confused. Here are the commands I have entered: > data <- read.csv(file="40609_sortedfinal.csv",head=TRUE,sep=",") > NumberOfActionsByStatus = data$STATUS > NumberOfActionsByUser = data$ETS_LOGIN > NumberOfBidOffer = data$BID_OFFER > NumberOfActionsByUser.freq = table(NumberOfActionsByUser) >

By considering this reproducible example #start code library(lattice) dotplot(variety ~ yield | site, data = barley, layout = c(1,6), index.cond= function(x,y){median(x)}, panel = function(x,y,...) { panel.dotplot(x,y,...) median.values <- median(x) panel.abline(v=median.values, col.line="red")

This is my reproducible example tv.ms<-structure(list(inq = structure(4:17, .Label = c("D4", "D5", "D6a", "D6b", "D6c", "D7", "D8", "F4", "F5a", "F5b", "F6a", "F6b", "F6c", "F6d", "F7a", "F7b", "F8"), class =