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fit lwr upr 1 218.4332 90.51019 346.3561 2 218.3906 90.46133 346.3198 3 218.3906 90.46133 346.3198 4 161.3982 44.85702 277.9394 5 192.4450 68.39903 316.4909 6 179.8056 56.49540 303.1158 7 219.5406 91.52707 347.5542 8 162.6761 46.65760 278.6945 9 193.8506 70.59838 317.1029 10 181.3816 58.11305 304.6502...

With this data x <- c(0,0,1,1,2,2) y <- c(5,6,4,3,2,6) lwr <- y-1 upr <- y+1 xlab <- c("Low","Low","Med","Med","High","High") mydata <- data.frame(x,xlab,y,lwr,upr) I would like to make a dot plot and use lwr and upr as error bars. Above 0=Low. I would like there to be some space between the 5 and...

...main groups [root@smb samba]# wbinfo -t checking the trust secret via RPC calls failed error code was NT_STATUS_ACCESS_DENIED (0xc0000022) Could not check secret The following works fine: [root@smb samba]# net ads info LDAP server: 10.50.0.190 LDAP server name: rcmroot1 Realm: RCM.UPR.EDU Bind Path: dc=RCM,dc=UPR,dc=EDU LDAP port: 389 Server time: Mon, 27 Feb 2006 13:56:33 VET KDC server: 10.50.0.190 Server time offset: 0 [root@smb samba]# net rpc info Domain Name: MYDOMAIN Domain SID: S-1-5-21-4214176146-1751683361-2990660170 Sequence number: 1345 Num users: 4786...

...ver, so I'm probably even running the same version of asterisk in both machines. Any advise? Someone else have a similar configuration working with Fedora Core 3? Thanks in advance, -- Jose R. Ortiz Ubarri (CHEO), CS System Administrator / Programmer High Performance Computing facility - UPR Email: Jose.Ortiz@hpcf.upr.edu|cheo@hpcf.upr.edu Phone: 787-758-3054 Fax: 787-758-3058

...+prb###it couldn't be this simple, could it? #by hand co=coef(ma)+coef(mb) new.sigma=sqrt(summary(ma)$sigma^2+summary(mb)$sigma^2) fit=co[1]+co[2]*yrs lwr= fit - qt(.975,9)*sqrt( new.sigma^2 * ( (1/11) + ( (yrs-mean(yrs))^2)/sum((yrs-mean(yrs))^2) ) )#the df are probably wrong (the 9 in the qt upr= fit + qt(.975,9)*sqrt( new.sigma^2 * ( (1/11) + ( (yrs-mean(yrs))^2)/sum((yrs-mean(yrs))^2) ) )# statement) I can't print the graph here, so here's code for it... #graph plot(a,ylim=c(0,1500)) points(b) lines(ma$fit) lines(mb$fit) lines(pra[,'lwr'],lty=2);lines(pra[,'upr'],...

...ws, where predw is the prediction from the fit that used 0-weights and preds is from using FALSE's in the subset argument. Is this difference proper? predw preds $fit $fit fit lwr upr fit lwr upr 1 1.544302 1.389254 1.699350 1 1.544302 1.194879 1.893724 2 1.935504 1.719482 2.151526 2 1.935504 1.448667 2.422341 $se.fit $se.fit 1 2...

....034)))) names(obs) <- c("X", "Y") ## Calculating t-dist, 2-tailed, 95% prediction intervals for new observations mse <- anova(mod)[2,3] new.x <- obs$X - mean(dat$X) sum.x2 <- sum((dat$X - mean(dat$X))^2) y.hat <- pred$fit var.y.hat <- mse*(1+new.x^2/sum.x2) upr <- y.hat + qt(c(0.975), df = 8) * sqrt(var.y.hat) lwr <- y.hat + qt(c(0.025), df = 8) * sqrt(var.y.hat) hand <- data.frame(cbind(y.hat, lwr, upr)) #The limits are not the same pred hand -- Thank you, Kurt [[alternative HTML version deleted]]

...someone on the mailing list that there will be a new release (3.023a) to fix this. Is this right?. If not, please let me know how to fix it. I need to solve this issue ASAP before trying to fix it manually for all the 500+ users. Thanks in advance. Regards, Richard Santiago rsantiago@rcm.upr.edu Richard Santiago Systems Administrator Information Systems Office University of Puerto Rico Medical Sciences Campus t. 787.758.2525 x. 2934 e. rsantiago@rcm.upr.edu <mailto:rsantiago@rcm.upr.edu>

...d of the Administrator account for the domain has changed. Does this has anything to do with my problems? Thanks for your prompt answer to my doubts and thanks for your help. Richard Santiago Systems Administrator University of Puerto Rico Medical Sciences Campus e. rsantiago at rcm dot upr dot edu

Hi everyone, I am trying to build a table putting standard errors horizontally. I haven't been able to do it. library(memisc) berkeley <- aggregate(Table(Admit,Freq)~.,data=UCBAdmissions) berk0 <- glm(cbind(Admitted,Rejected)~1,data=berkeley,family="binomial") berk1 <- glm(cbind(Admitted,Rejected)~Gender,data=berkeley,family="binomial") berk2 <-

...07-15 02:43:25.055207448 -0300 @@ -66,10 +66,12 @@ center <- center[keep] width <- qtukey(conf.level, length(means), x$df.residual) * sqrt((MSE/2) * outer(1/n, 1/n, "+"))[keep] - dnames <- list(NULL, c("diff", "lwr", "upr")) + est <- center/(sqrt((MSE/2) * outer(1/n, 1/n, "+"))[keep]) + pvals <- ptukey(abs(est),length(means),x$df.residual,lower.tail=FALSE) + dnames <- list(NULL, c("diff", "lwr", "upr","p adj")) if (!is.null...

...Ten en cuenta que el 2do tipo de intervalos de calcula para observaciones _futuras_. En R puedes calcularlos de la siguiente manera: ## IC de confianza## ver ?predict.lm para mas detallesR> data.frame(y, predict(modelo, interval = "confidence")) y fit lwr upr#1 8.35 9.938571 6.580445 13.29670#2 12.42 11.804286 9.134239 14.47433#3 18.00 15.535714 13.664949 17.40648#4 17.58 17.401429 15.396872 19.40599#5 17.97 19.267143 16.798908 21.73538#6 20.76 21.132857 18.014915 24.25080 ## intervalos de prediccion para x = 25 R> predict(modelo, newdata = data....

...mCREB 7 1.0000000 No Virus 8 1.0000000 No Virus 9 1.0000000 No Virus > TukeyHSD(aov(Values ~ ind, data = nmda456)) Tukey multiple comparisons of means 95% family-wise confidence level Fit: aov(formula = Values ~ ind, data = nmda456) $ind diff lwr upr p adj mCREB-CREB -6.0666126 -6.3289033 -5.8043219 0.0000000 No Virus-CREB -5.3921477 -5.6544383 -5.1298570 0.0000000 No Virus-mCREB 0.6744649 0.4121743 0.9367556 0.0005382 > TukeyHSD(aov(Values ~ ind, data = nmda123)) Tukey multiple comparisons of means 95% family-wise conf...

Hi, 1. How do I construct 95% prediction interval for new x values, for example - x = 30000? 2. How do I construct 95% confidence interval? my dataframe is as follows : >dt structure(list(y = c(26100000, 60500000, 16200000, 30700000, 70100000, 57700000, 46700000, 8600000, 10000000, 61800000, 30200000, 52200000, 71900000, 55000000, 12700000 ), x = c(108000, 136000,

...= rev(range(0:100)), xlab="CHAO", ylab="Depth", pch=15, las=2, main="Sep12-RNA", cex.main=1) > lmR <- lm(cd$Depth~cd$CHAOsep12RNA) > abline(lmR) pconfR <- predict(lmR,interval="confidence") matlines(cd$CHAOsep12RNA,pconfR[,c("lwr","upr")], col=1, lty=2) I also tried > newx <- seq(min(cd$CHAOsep12RNA), max(cd$CHAOsep12RNA), length.out=11) > a <- predict(lmR, newdata=data.frame(CHAO=newx), interval=c("confidence")) > plot(cd$CHAOsep12RNA,cd$Depth, ylim = rev(range(0:100)), xlab="CHAO", ylab...

...lab=2, xlab="Residual Q95") I am trying to plot the results in lattice for publication purposes so I need to figure this out. I have been struggling but I think I have reached a dead end.? Here is what I have been able to code: M<-predict(model$gam,type="response",se.fit=T) upr<- M$fit + (1.96 * M$se.fit)lwr<- M$fit - (1.96 * M$se.fit) library(lattice)xyplot(fitted(model$gam) ~ Q95 |super.end.group, data = spring, gm=model,? ? ? ?prepanel=function (x,y,...)list(ylim=c(min(upr),max(lwr))),? ? ? ?panel = function(x,y, gm, ...){ ? ??? ? ? ? ?panel.xyplot(x,y, type=&quo...

...0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 > TukeyHSD(fm1,conf.level=0.90) Tukey multiple comparisons of means 90% family-wise confidence level Fit: aov(formula = breaks ~ wool * tension, data = warpbreaks) $wool diff lwr upr p adj B-A -5.777778 -10.77183 -0.7837284 0.058213 $tension diff lwr upr p adj M-L -10.000000 -17.66710 -2.332900 0.0228554 H-L -14.722222 -22.38932 -7.055122 0.0005595 H-M -4.722222 -12.38932 2.944878 0.4049442 $`wool:tension` diff lwr u...

I know that there are some patches being worked on to cache realtime users that might ultimately fix this problem, but until then, here is a little script that brings back the MWI when using the excellent mysql realtime architecture with sip: http://www.cheapnet.net/~mike/asterisk/send_mwi.txt This script relies on sipsak utility found at http://sipsak.berlios.de/ Download, rename to

Como usas la función image puedes consultar la ayuda ?image o help(image) y encontrarás el siguiente ejemplo donde se usa un diferente color Palette (mencionada por pepeceb en su respuesta). x <- 10*(1:nrow(volcano)) y <- 10*(1:ncol(volcano)) image(x, y, volcano, col = terrain.colors(100), axes = FALSE) # O puedes usar directamente el número para indicar el color image(x, y, volcano, col =

...- When resolving names via dns_resolv uses the search path if there's no dot in the name. - Reverts to the previous behaviour in the absence of a search path, if the name contains a dot or if no addresses are found when searching the domain search path. Steve Bleazard -- diff -upr syslinux-6.03.orig/core/fs/pxe/dhcp_option.c syslinux-6.03/core/fs/pxe/dhcp_option.c --- syslinux-6.03.orig/core/fs/pxe/dhcp_option.c 2014-10-06 17:27:44.000000000 +0100 +++ syslinux-6.03/core/fs/pxe/dhcp_option.c 2016-01-04 07:58:18.158206039 +0000 @@ -7,6 +7,11 @@ #include "pxe.h" c...