similar to: how to skip a numeric column for averaging other columns?

Hi, I am thinking about IWLS vs ML estimation. When I use glm() for a 2-parameter distribution (e.g., Weibull), I can otain the MLE of scale parameter given shape parameter through IWLS. Because this scale parameter usually converges to the MLE. In this point, I am wondering: i) can you say that the direct MLE, which is obtained by maximizing a likelihood function, is equalvant to the indirect

Hi there, The data is data<-c(2,6,13,26,19,25,18,11,22,25) I want to count data for these rages: [0~10]: [11~20]: [21-30]: Is anyone can help me? Thank you in advance -- View this message in context: http://www.nabble.com/count-data-with-a-specific-range-tp19732290p19732290.html Sent from the R help mailing list archive at Nabble.com.

I'm sorry everyone for the inconvenience of spamming the R-help... Here's the complete post: Hi everyone, > > Since it's quite a while that I used the reshape package, I now feel kind > of rusty. > > I have a data.frame like this: > > > > id Sample.Name Marker Allele.1 > Allele.2 sample_id species

Is there anyone knowing a function or way for standard normal cumulative distribution? ?(z=-0.1)=? also ?(z=?)=0.025 Thank you, -- View this message in context: http://www.nabble.com/calculation-for-standard-normal-cumulative-distribution-tp20282804p20282804.html Sent from the R help mailing list archive at Nabble.com.

Hi all, Probably a simple question, but I just can't find a simple answear in the older threads or anywhere else. I've added some new vectors as columns in a data frame using cbind(). As they're all put as the last columns inte the data frame, I would like to move them to specific positions. How do you do to change the position of a column in a data frame? I know I can use

I have hundreds of humans who have undergone SNP genotyping at hundreds of loci. Some have even undergone the procedure twice or thrice (kind of an internal control). So obviously I need to find those replications, and confirm that the results are the same. If there is discordance then I need to address it. I tried to use the aggregate function nr.attempts

Hi, I have a page were users can start jobs that may take several hours to run. BackgrounDrb is perfect for me and seems to be working well most of the time but some times I have the following problem: My worker is set up like this: class UploadWorker < BackgrounDRb::MetaWorker set_worker_name :upload_worker set_no_auto_load(true) def create(args = nil ) file = args[:file]

hi guys..please help me with this i am working on two data frames one goes like this: DF1 Sample_id RepairHours Denatured Dose ZeroMean FourtyFiveMean NinetyMean 1 SDM071 0 1 B 60.5 19.0 45.0 2 SDM071 1 1 B 46.0 23.0 42.5 3 SDM071 2 1 B 52.5 24.0 40.0 4 SDM071

Hi everyone, I have an issue with a data conversion. First, I tried it with the reshape-package, but since it's quite a while that I used it, I feel kind of rusty... I have a data.frame like this: id Sample.Name Marker Allele.1 Allele.2 sample_id species 1 01_primer01 Dalb01 165 179

I have a dataset called "raw-data" . I am trying to use the following code - col_name<-names(raw_data) for (i in 1:(length(names(raw_data))-2)) { tbl=table(raw_data$Pay.Late.Dummy, raw_data$col_name[i]) chisqtest<-chisq.test(tbl) } Say the 1st column of my raw_data is Column1. The idea is when i=1 then raw_data$col_name[i] will automatically become raw_data$Column1 ,

Quantreggers: I'm trying to run rq() on a dataset I posted at: https://docs.google.com/file/d/0B8Kij67bij_ASUpfcmJ4LTFEUUk/edit?usp=sharing (it's a 1500kb csv file named "singular.csv") and am getting the following error: mydata <- read.csv("singular.csv") fit_spl <- rq(raw_data[,1] ~ bs(raw_data[,i],df=15),tau=1) > Error in rq.fit.br(x, y, tau = tau, ...) :

Greetings all, I am getting this error that is driving me nuts... (not a long trip, haha) I have a set of files and in these files I want to calculate ttests on rows 'compareA' and 'compareB' (these will change over time there I want a variable here). Also these files are in many different directories so I want a way filter out the junk... Anyway I don't believe that this is

Hello, I am trying to import data from an SQLite database to R. Unfortunately, I seem to get wrong data when I try to import very large numbers. For example: I look at the database via SQLiteStudio(v.1.1.3) and I see the following values: OrderID Day TimeToclose 1 2009-11-25 29467907000 2 2009-11-25 29467907000 3 2009-11-25 29467907000 Now I run this R Code: >

Hi, I''m trying to stub File.open and whenever I do, rspec blows up with the following error message (undefined method `add'' for nil:NilClass), which seems to happen because method __add in class Proxy is calling #add on global $rspec_mocks, which in turn is nil. Can someone explain what I''m doing wrong, as I can''t seem to stub anything out! Here''s

Hello, I do have two different time series A and B, they are different in length and starting point. A starts in Jan, 2012 and ends in Dec, 2012 and B starts in March, 2012 and ends in Nov, 2012. How can I plot those two series A and B in the same plot? I.E., from Jan. 2012 - Feb, 2012, it would have one data point from A and from Mar, 2012-Nov, 2012, it would have two data points from A and B,

Hi R -users, i've a table as describe below. I'm reading the numeric value presented in this table to populate a list. #table #============ #X    A    B    C #x1    2    3    4 #x2    5    7    10 #x4    2    3    5 #============ rawData <- read.table("raw_data.txt",header=T, sep="\t") myList=list() counter=0 for (i in c(1:length(rawData$X))) {     print (i)    

I have an error for a simple optimization problem. Is there anyone knowing about this error? lambda1=-9 lambda2=-6 L<-function(a){ s2i2f<-(exp(-lambda1*(250^a)-lambda2*(275^a-250^a)) -exp(-lambda1*(250^a)-lambda2*(300^a-250^a))) logl<-log(s2i2f) return(-logl)} optim(1,L) Error in optim(1, L) : function cannot be evaluated at initial parameters Thank you in advance -- View this

I am trying to create a barplot displaying the sums of 2 columns of data grouped by a variable. the data is set up like this: "city" "n" "y" <br> mon 100 200 <br> tor 209 300 <br> edm 98 87 <br> mon 20 76 <br> tor 50 96 <br> edm 62 27 <br> the resulting plot should have city as the x-axis, 2 bars per city, 1 representing

I use "while" loop but it produces an errro. I have no idea about this. Error in "[<-"(`*tmp*`, i, value = numeric(0)) : nothing to replace with The problem description is The likelihood includes two parameters to be estimated: lambda (=beta0+beta1*x) and alpha. The algorithm for the estimation is as following: 1) with alpha=0, estimate lambda (estimate beta0

# need zoo to use rollapply() # your data (I called df) df <- structure(list(a = 1:2, b = 2:3, c = c(5L, 9L), d = c(9L, 6L), e = c(1L, 5L), f = c(4, 7)), .Names = c("a", "b", "c", "d", "e", "f"), class = "data.frame", row.names = c(NA, -2L)) # transpose and make a zoo object df2 <- zoo(t(df)) #rollapply to get