similar to: regression

Hi dear all, It may be a simple question, i have a list output with different number of elements as following; [[1]] [1] 0.86801402 -0.82974691 0.39746666 -0.98566707 -4.96576856 -1.32056754 [7] -5.54093319 -0.07600462 -1.34457280 -1.04080125 1.62843297 -0.20473912 [13] 0.30659907 2.66908117 2.53791837 0.53788013 -0.57463077 0.27708874 [19] -2.94233200 1.54565643 -6.83694100

Hi Dear All, This is a function which contains Covariance Ratio and Likelihood Distance values (CVRi, LDi). i want to compute the all row's values, that is run this function for nrow(X) times. The X and Y matrices are;

Hi Dear All, Can someone give me a suggestion about which robust statistics are most appropriate for outlier detection in linear models, and is available with R ? Thanks for any idea. -- View this message in context: http://r.789695.n4.nabble.com/Robust-Statistics-for-Outlier-Detection-tp3438493p3438493.html Sent from the R help mailing list archive at Nabble.com.

Hi dear all, i have a data (data.frame) which contain y and x coloumn(i.e. y x 1 0.58545723 0.15113102 2 0.02769361 -0.02172165 3 1.00927527 -1.80072610 4 0.56504053 -1.12236685 5 0.58332337 -1.24263981 6 -1.70257274 0.46238255 7 -0.88501561 0.89484429 8 1.14466282 0.34193875 9 0.58827457 0.15923694 10 -0.79532232 -1.44193770 ) i changed

Hi dear all, Can aynone help me about delete-d jackknife usually normal jackknife code for my data is: n <- nrow(data) y <- data$y z <- data$z theta.hat <- mean(y) / mean(z) print (theta.hat) theta.jack <- numeric(n) for (i in 1:n) theta.jack[i] <- mean(y[-i]) / mean(z[-i]) bias <- (n - 1) * (mean(theta.jack) - theta.hat) print(bias) but how i can apply delete-d jackknife

Hi everyones, my function like; e <- rnorm(n=50, mean=0, sd=sqrt(0.5625)) x0 <- c(rep(1,50)) x1 <- rnorm(n=50,mean=2,sd=1) x2 <- rnorm(n=50,mean=2,sd=1) x3 <- rnorm(n=50,mean=2,sd=1) x4 <- rnorm(n=50,mean=2,sd=1) y <- 1+ 2*x1+4*x2+3*x3+2*x4+e x2[1] = 10 #influential observarion y[1] = 10 #influential observarion data.x <- matrix(c(x0,x1,x2,x3,x4),ncol=5) data.y

Hi, We recently found a testcase showing that simplifications in instcombine sometimes change the instruction without reducing the instruction cost, but causing problems in TwoAddressInstruction pass. And it looks like the problem is generic and other simplification may have the same issue. I want to get some ideas about what is the best way to fix such kind of problem. The testcase:

On Wed, Aug 2, 2017 at 3:36 PM, Matthias Braun <mbraun at apple.com> wrote: > So to write this in a more condensed form, you have: > > %v0 = ... > %v1 = and %v0, 255 > %v2 = and %v1, 31 > use %v1 > use %v2 > > and transform this to > %v0 = ... > %v1 = and %v0, 255 > %v2 = and %v0, 31 > ... > > This is a classical problem with instruction

I have a ror project which has been productized. There are several web sites in one ror project I need to set an "enviroment variable" to run different sites, can I do that using mongrel? I tried to use mongrel''s -S option and set the enviroment variable in that file but it seems mongrel runs that file after it calls enviroment.rb I also used apache''s

Hi there, I have been using the example provided bellow for a while, and It was working without any problem. Nevertheless, just since 2-3 days is not working, probably because I did update.packages(). I have tried to re-install the older versions of the packages Hmisc() and xtable(), but still does not work. Can you run this example, and tell me if you got the same problems? I use

Op 19-10-2016 om 13:47 schreef Matthew Broadhead: > i am not 100% sure how to give you the information you require. > > my current setup in /etc/postfix/master.cf is > flags=DRhu user=vmail:mail argv=/usr/libexec/dovecot/deliver -d > ${recipient} > so recipient would presumably be user at domain.tld? or do you want the > real email address of one of our users? is there

Hi, In the example you showed: m1<- matrix(0,length(vec),max(vec)) 1*!upper.tri(m1) #or ?m1[!upper.tri(m1)] <-? rep(rep(1,length(vec)),vec) #But, in a case like below, perhaps: vec1<- c(3,4,5) ?m2<- matrix(0,length(vec1),max(vec1)) ?indx <- cbind(rep(seq_along(vec1),vec1),unlist(tapply(vec1,list(vec1),FUN=seq),use.names=FALSE)) m2[indx]<- 1 ?m2 #???? [,1] [,2] [,3] [,4] [,5]

Hi, I' am interested in differences between sample's result when samples consist of full elements and consist of only distinct elements. When sample consist of full elements it take about 120 sec., but when consist of only distinct elements it take about 4.5 or 5 times more sec. I expected that opposite of this result, because unique(sample) has less elements than full sample. Code as

Hello gurus, I have some variables, and i am creating combinations for analysis in the end i need these variables to be displayed like "LEPTIN+SAA+PTH". currently i am using loop to perform this. I would appreciate any pointers to do it without the loop. > mols=c("LEPTIN","SAA","PTH","sEGFR") > samples=mols[1:3] > samples [1]

the server is using CentOS 7 and that is the package that comes through yum. everything is up to date. i am hesitant to install a new package manually as that could cause other compatibility issues? is there another way to test the configuration on the server? On 21/10/2016 01:07, Stephan Bosch wrote: > Op 10/20/2016 om 7:38 PM schreef Matthew Broadhead: >> do i need to provide

do i need to provide more information? On 19/10/2016 14:49, Matthew Broadhead wrote: > /var/log/maillog showed this > Oct 19 13:25:41 ns1 postfix/smtpd[1298]: 7599A2C19C6: > client=unknown[127.0.0.1] > Oct 19 13:25:41 ns1 postfix/cleanup[1085]: 7599A2C19C6: > message-id=<edc55a9b-eb49-3945-dc60-0e1d51a78e97 at nbmlaw.co.uk> > Oct 19 13:25:41 ns1 postfix/qmgr[1059]:

is there something more i need to be doing my end? On 25/10/2016 09:11, Matthew Broadhead wrote: > are there any instructions or tests i can make to check the sieve > configuration? or does the magic all happen internally and there are > no settings to change? > > On 21/10/2016 10:22, Matthew Broadhead wrote: >> the server is using CentOS 7 and that is the package that

Hi all, I am doing bootstrap with logistic regression by using glm function, and I get the errors; glm.fit: fitted probabilities numerically 0 or 1 occurred and glm.fit: algorithm did not converge I have read some things about this issue in the mailing list. I can guess what was the problem. My data contains one or may be two outliers. Does the error occur due to these extreme values or

Dear users, In my psychometric test i have applied logistic regression on my data. My data consists of 50 predictors (22 continuous and 28 categorical) plus a binary response. Using glm(), stepAIC() i didn't get satisfactory result as misclassification rate is too high. I think categorical variables are responsible for this debacle. Some of them have more than 6 level (one has 10 level).

Hi guys, I''m looking for a way to pass environment variables to my Rails app via Mongrel. I want to conditionally execute code in environment.rb based on these environment variables. Background: 1. I have some special stuff I want to do when my Rails app first starts 2. So, stuff it in environment.rb in after_initialize, right? 3. Not this time. I have several other background