similar to: finding the annual maximun within several years

I'm using asteriskathome 2.5. I'm using 2 spa3000 for dialing-out. I configured a trunk for each one with maximun channels=1 and an outbound route that includes both trunks. When a second outgoing call is placed, Asterisk tries to place it in the same that is already in use resulting in a busy tone. ?What can be the problem? -- Alejandro Vargas

Dear Mr. Baddeley   I just graduated from a Masters in Applied Mathematics on Jun19th. My thesis was about spatial distribution /a nalysis of some trees in a part of  the Congo Basic Forest. In my thesis I used your spatial package in R, and today I'm doing a more deeper study about how we choise the r distance in Function F(). I would like to be able to understand about value of rmaxdefault

dear kind helper, i would like to know how to find the annual maximun for a table that basicly looks like this: date time measurement1 measurement2 measurement3 mm/dd/yyyy hh:mm:ss m1 m2 m3 there are about 9000 measurements for each year, which makes it quite large... i already tried to subset all rows for a year, to find the maximum within these choosen rows, y <-

I have a data set for different time intervals. The data has three comment lines before data for each time interval. For each time interval there are 500 data points. I want to change the dataset such that I have the following format: t1 t2 t3 ................ 0.00208 0.00417 0.00625 ................. a1 a2 a3 ...................

I''m moving some data off an old machine to something reasonably new. Normally, the new machine performs better, but I have one case just now where the new system is terribly slow. Old machine - V880 (Solaris 8) with SVM raid-5: # ptime du -kds foo 15043722 foo real 6.955 user 0.964 sys 5.492 And now the new machine - T5140 (latest Solaris 10) with ZFS

Dear R users, I'm trying to fit a set an ODE to an experimental time series. In the attachment you find the R code I wrote using modFit and modCost of FME package and the file of the time series. When I run summary(Fit) I obtain this error message, and the values of the parameters are equal to the initial guesses I gave to them. The problem is not due to the fact that I have only one

Hi, I am new in statistics and i manage to make the linear model analysis but i have some difficulties in explaining the results. Can someone help me explalinig the output of my linear model analysis ? My data are with 2 variables habitat (e,s) and treatment (a,c,p) with multiple trials within. Thank you in advance Call: lm(formula = a$wild ~ a$habitat/a$treatment/a$trial) Residuals: Min

I have 11 possible predictor variables and use them to model quite a few target variables. In search for a consistent manner and possibly non-manual manner to identify the significant predictor vars out of the eleven I thought the option "select=T" might do. Example: (here only 4 pedictors) first is vanilla with "select=F" >

Hi, I just read the "Embedding R in Gnumeric" idea at http://www.r-project.org/SoC08/ideas.html. On my side, I intend to add as many statistics related plot types to the current gnumeric charting engine as possible. We already have boxplots and partial support for histograms. My immediate plans are to finish the histogram code and add probability plots

Hello dear R members. I have been learning the Anova syntax in order to perform an SS type III Anova with repeated measures designs (thank you Prof. John Fox!) And another question came up: where/what are the (between/within) residuals for my model? ############ Play code: phase <- factor(rep(c("pretest", "posttest", "followup"), c(5, 5, 5)),

> -----Original Message----- > From: William Dunlap > Sent: Tuesday, November 25, 2008 9:16 AM > To: 'johannes_graumann at web.de' > Subject: Re: [R] Efficient passing through big data.frame and > modifying select fields > > > Johannes Graumann johannes_graumann at web.de > > Tue Nov 25 15:16:01 CET 2008 > > > > Hi all, > > > >

Dear All- I have a dataset that is comprised of the following: doy yr mon day hr hgt1 hgt2 hgt3 co21 co22 co23 sig1 sig2 sig3 dif flag 244.02083 2005 09 01 00 2.6 9.5 17.8 375.665 373.737 373.227 3.698 1.107 0.963 -0.509 PRE 244.0625 2005 09 01 01 2.6 9.5 17.8 393.66 384.773 379.466 15.336 11.033 5.76 -5.307 PRE 244.10417 2005 09 01 02 2.6 9.5 17.8 411.162 397.866 387.755 6.835 5.61 6.728

pulling my hair out... If I rm -fr /root/.spamassassin/* then sa-learn a bunch of messages, it works... ]# sa-learn --dump magic 0.000 0 3 0 non-token data: bayes db version 0.000 0 3997 0 non-token data: nspam 0.000 0 0 0 non-token data: nham 0.000 0 202022 0 non-token data: ntokens 0.000

Hello R users, For the last few days I am struggling with the following task: my data.frame: A1 A2 A3 B1 B2 B3 58.81 53.292 54.501 13.013 17.39 19.407 56.02 56.251 54.033 20.099 13.15 10.411 55.376 53.099 57.625 13.396 21.031 13.22 58.584 53.194 54.218 13.038 16.854 19.289 55.7 55.921 53.847 19.942 13.153 9.828 55.093 52.934

In the summary of the gam object produced by gamm, the "Approximate significance of smooth terms" appears to be a test of the improvement in fit over a linear model, rather than a test of the significance of the overall effect of x on y: test.gamm<-gamm(y~te(x, bs="cr"), random=list(grp=~1)) summary(test.gamm$gam) . . . Approximate significance of smooth terms:

Hello R-help I don’t know how to interpret significance from the contr.poly() function . From the example below : how can I tell if data has a significant Linear/quadratic/cubic trend? > contr.poly(4, c(1,2,4,8))               .L         .Q          .C [1,] -0.51287764  0.5296271 -0.45436947 [2,] -0.32637668 -0.1059254  0.79514657 [3,]  0.04662524 -0.7679594 -0.39757328 [4,]  0.79262909 

* Apologies for multiple posting * I attached to my previous e-mail a .r file, and it was not permitted by the rules of the mailing lis. Again, please receive my sincere apologies for this. I re-send again the e-mail with .txt attachemnt in the hope someone an help me to solve my problem. I'm trying to fit a set an ODE to an experimental time series. In the attachment you find the R code I

Andy and I briefly discussed this the other day, we have not yet got chance to list a detailed pass order for the pre- and post- IPO scalar optimizations. This is wish-list in our mind: pre-IPO: based on the ordering he propose, get rid of the inlining (or just inline tiny func), get rid of all loop xforms... post-IPO: get rid of inlining, or maybe we still need it, only

ABCD are four matrix. A * Inverse((Transpose(A)*Tranpose(B)*B*A+C)) * Transpose(A) * Transpose(B) * D how to write in R in an efficient way? --------------------------------- [[alternative HTML version deleted]]

I have the following: Time A1 A1 B1 B1 C1 C2 x y x y x y 0 5 6 6 7 7 9 1 3 4 4 3 9 9 2 5 2 6 4 7 4 I want to change it to the following: 0 1 2 x y x y x y A1 5 6 3 4 5 2 B1