similar to: How to calculate the concentration

Our domain controllers have run samba 4.4.3 since it was released. We didn't upgrade because it was so stable :) I recently decided that release was too old and upgraded to 4.8.2 (then current). Our domain controllers were crashing on 4.8.2 so I upgraded to 4.8.3 as soon as it was released but this has not resolved the issue. When the issue occurs the DC becomes unresponsive and needs to be

Suppose I have two columns of entries, how can I get the union of the two columns? Please note: I input my columns through excel. These entries have text format in excel. Also, out of curiosity, how can I find out the data type of a data frame ? > a <- read.csv("book1.csv") > a n1 n2 1 apple soda 2 orange apple 3 soda green 4 red yellow 5 white blue 6

I would like to prepare the data for barplot. But I only have the data frame now. x1=rnorm(10,mean=2) x2=rnorm(20,mean=-1) x3=rnorm(15,mean=3) data=data.frame(x1,x2,x3) If there a way to put data within a specific range? The expected result is as follows: range x1 x2 x3 -10-0 2 5 1 (# points in this

Hi, folks, As seen in the following codes: x1=rlnorm(10) x2=rlnorm(10,mean=2) y=rlnorm(10,mean=10)### Fake dataset linmod=lm(log(y)~log(x1)+log(x2)) After the regression, I would like to know the mean of y. Since log(y) is normal and y is lognormal, I need to know the mean and variance of log(y) first. I tried mean (y) and mean(linmod), but either one is what I want. Any tips? Thanks in

Dear all, Suppose my data frame is as follows: id price distance 1 2 4 1 3 5 ... 2 4 8 2 5 9 ... n 3 7 n 8 9 I would like to calculate the rank-order correlation between price and distance for each id. cor(price,distance,method = "spearman") calculate a correlation for all. Then I tried to use apply(data,list='id',cor(price , distance , method =

Hi Everyone, I am new to R Language and was wondering if someone could help me convert my latitude-longitude coordinates to cartesian coordiantes using geoXY() from SoDA package? I have been uploading my coordinates from a text file into R (they originate as a dataframe) and them converting them to a matrix using the data.matrix() function. But I think I'm running into trouble when I try to

Hi, folks, As I understand, Least-squares Estimate (second-moment assumption) and the Method of Maximum Likelihood (full distribtuion assumption) are used for linear regression. I do >?lm, but the help file does not tell me the model employed in R. But in the book 'Introductory Statistics with R', it indicates R estimate the parameters using the method of Least-squares. However it

Recently I setup samba 2.23 on a Red Hat 7.3 machine to be the Primary Domain controller, my win2k machine logs in just fine with username and password I setup sees the shares it should, however the problem I have is if I try to copy something to one of the shares it copies hte file 3 times, one is the origianl one is blank, one is coded and is the same file. And I can't seem to figure this

Dear R People: I'm sure that this is a very silly question, but I'm reading the Software for Data analysis book by John Chambers, and I can't find the "Declination" data that he refers to on page 15 in the book. I did all of the usual stuff: library(help=SoDA) ??Declination looked for it online but to no avail. Has anyone else run into this, please? Any help would be

Hi, folks, Here are the codes: ############## y=1:10 x=c(1:9,1) lin=lm(log(y)~x) ### log(y) is following Normal distribution x=5:14 prediction=predict(lin,newdata=x) ##prediction=predict(lin) ############### 1. The codes do not work, and give the error message: Error in eval(predvars, data, env) : numeric 'envir' arg not of length one. But if I use the code after the pound sign, it

Hi everybody, I'm running an old game called SODA Off-Road Racing in Wine. Everything runs perfectly in the game, except networking. I added test results for it to the AppDB. Does anyone know of anything I can try to get networking working properly in the game? So far I've tried a suggestion from the Wine FAQ to change /etc/hosts to show my IP instead of a loopback address.

I am using the package rpart to explore various classification structures. The call looks like: seekhi1<-rpart(pvol~spec+a1+psize+eppres+numpt+icds+bivalcrt+stents+ppshare+ nhosp+nyrs,data=dat,method="class", control=rpart.control(minsplit=30,xval=10)) The output is 1) root 198 87 1 (0.5606061 0.4393939) 2) psize=1,2 122 43 1 (0.6475410 0.3524590)

After a user changes their password (CTRL-ALT-DEL) in our Samba 4 domain (4.1.12) they lose access to any stored passwords on their Windows PC. I've set the log level in smb.conf to 4 and enabled the GPO to record DPAPI log entries in Windows to get the below log data. My reading of the two is that the Windows PC believes it is failing to reset the access to its DPAPI store (where the saved

Hi all, I have an issue with the lm() function regarding the listing of the coefficients. My data are below, showing a list of hours (HR) relating to the time spent resting (R) by an individual animal. Simply i want to run a lm() to run in an anova() to see if there is a significant difference in resting between hours. HR R 1 2 0.6666667 2 2 0.4666667 3 2 0.8000000 4 2

I must have a misunderstanding of partials, maybe one of you can help me out. I have a page that initially displayed via the following: <-- in controller --> def find_areas_for_country @country_areas = CountryArea.find(:all, :conditions => ["country_id = :country", params], :order => "descr asc") render :partial => ''country_area''

could somebody please advise me on the following thing: there's one ogg vorbis music file (a long mix). it is split into many parts with tobias' ogg cutter. the parts get tagged and the many files are again combined into one. the purpose of this would be that when playing back the such combined file, the player should display the individual tags while it's still a single track.

Hi all, I have a question about standardization. Suppose I have training data which is a X matrix, of size N x p, where N is the number of samples, p is the number of variables in the data set. Y is a response vector of size N x 1, each element correspoding to each row of the X matrix. I do standardization on X, X1=scale(X, TRUE, TRUE), and Y1=scale(Y, TRUE, FALSE). And I got a regression

Hi, folks linmod=y~x+z summary(linmod) The summary of linmod shows the standard error of the coefficients. How can we get the sd of y and the robust standard errors in R? Thanks! [[alternative HTML version deleted]]

Hi, folks, Please first look at the codes: plan_a=c('apple','orange','apple','apple','pear','bread') plan_b=c('bread','bread','orange','bread','bread','yogurt') value=1:6 data=data.frame(plan_a,plan_b,value) library(plyr) library(reshape) mm=melt(data, id=c('plan_a','plan_b'))

Hi, folks, runif (n,min,max) is the typical code for generate R.V from uniform dist. But what if we need to fix the mean as 20, and we want the values to be integers only? Thanks [[alternative HTML version deleted]]