similar to: adding labels to x,y points

Hi, See below I reply your message for <https://stat.ethz.ch/pipermail/r-help/2008-April/160966.html>[R] predict.glm & newdata posted on Fri Apr 4 21:02:24 CEST 2008 You say it ##works fine but it does not: if you look at the length of yhat2, you will find 100 and not 200 as expected. In fact predict(reg1, data=x2) gives the same results as predict(reg1). So I am still looking for

Hello, I have two problems in automating multiple glm(s) operations. The data file is tab delimited file with headers and two columns. like "ABC" "EFG" 1 2 2 3 3 4 dat <- read.table("FILENAME", header=TRUE, sep="\t", na.strings="NA", dec=".", strip.white=TRUE) dataf <- read.table("FILENAME", header=FALSE,

Hello All: This series is an update version of multiqueue virtio-net driver based on Krishna Kumar's work to let virtio-net use multiple rx/tx queues to do the packets reception and transmission. Please review and comments. Test Environment: - Intel(R) Xeon(R) CPU E5620 @ 2.40GHz, 8 cores 2 numa nodes - Two directed connected 82599 Test Summary: - Highlights: huge improvements on TCP_RR

Hello All: This series is an update version of multiqueue virtio-net driver based on Krishna Kumar's work to let virtio-net use multiple rx/tx queues to do the packets reception and transmission. Please review and comments. Test Environment: - Intel(R) Xeon(R) CPU E5620 @ 2.40GHz, 8 cores 2 numa nodes - Two directed connected 82599 Test Summary: - Highlights: huge improvements on TCP_RR

Hello, I want to use pearson's correlation as distance between observations and then use any centroid based linkage distance (ex. Ward's distance) When linkage distances are formed as the Lance-Williams recursive formulation, they just require the initial distance between observations. See here: http://en.wikipedia.org/wiki/Ward%27s_method It is said that you have to use euclidean

Dear All, I have the following data coming out from s <- with(final, summarize(norm, llist(gtt,fdiab), function(norm) { n <- sum(!is.na(norm)) s <- sum(norm, na.rm=T) binconf(s, n) }, type='matrix') ) ie gtt fdiab norm.norm norm.norm2 norm.norm3 18

Hi, I'm having a bit of trouble with the axes in my plots. I don't like the way R does not have them cross in the origin. Is there another plot/axis function? i tried using abline as suggested by someone from this list, but in my case this gives no satisfactory result, as the abline does sometimes lie on top of the y axis and sometimes not, depending on how i scale the image... #bild16

Hi, I'm trying to melt() some data for subsequent cast()ing and am encoutering errors. The overall process requires a couple of casts()s and melt()s. ########Start Session 1########## ## I have the data in a (fully) melted format and can cast it fine... > norm1[1:10,] Pool SNP Sample.Name variable value 1 1 rs1045485 CA0092 Height.1 0.003488853 2 1 rs1045485

Hi all - I'm stumped by the following mdl <- glm(resp ~ . , data = df, family=binomial, offset = ofst) WORKS yhat <- predict(mdl) WORKS yhat <- predict(mdl,newdata = df) FAILS Error in drop(X[, piv, drop = FALSE] %*% beta[piv]) : subscript out of bounds I've tried without offset, quoting binomial. The offset variable ofst IS in df. Previous postings indicate possible

Hi I Have a very large dataset that I would like to conduct ANOVA tests on. Im not a very strong programmer so any help would be appreciated. the format is Identifier             A1       A2        B1      B2       C1   C2      Norm1         Norm2 1234                  1        1            NA     NA      4       3        NA               NA 4567                  2        2              4     

How can I get the result of, e.g., poly(1:3. degree=2) to give me the unnormalized integer coefficients usually used to explain orthogonal polynomial contrasts, e.g, -1 1 0 -2 1 1 As I understand things, the columns of x^{1:degree} are first centered and then are normalized by 1/sqrt(col sum of squares), but I can't see how to relate this to what is returned by poly(). >

Hello All: This series is an update version of multiqueue virtio-net driver based on Krishna Kumar's work to let virtio-net use multiple rx/tx queues to do the packets reception and transmission. Please review and comments. Test Environment: - Intel(R) Xeon(R) CPU E5620 @ 2.40GHz, 8 cores 2 numa nodes - Two directed connected 82599 Test Summary: - Highlights: huge improvements on TCP_RR

Hello All: This series is an update version of multiqueue virtio-net driver based on Krishna Kumar's work to let virtio-net use multiple rx/tx queues to do the packets reception and transmission. Please review and comments. Test Environment: - Intel(R) Xeon(R) CPU E5620 @ 2.40GHz, 8 cores 2 numa nodes - Two directed connected 82599 Test Summary: - Highlights: huge improvements on TCP_RR

Hello everyone, I have a data frame in which I am wanting to eliminate the row labels and then relabel the rows with g1-g2000.I have used the following code: dat<-read.table(file="C:\\Documents and Settings\\Owner\\My Documents\\colon cancer1.txt",header=T,row.names=1) file.show(file="C:\\Documents and Settings\\Owner\\My Documents\\colon cancer1.txt") I thought that this

I have a function that fits polynomial models for the orders in n: lmn <- function(d,n){ models=list() for(i in n){ models[[i]]=lm(y~poly(x,i),data=d) } return(models) } My data is: > d=data.frame(x=1:10,y=runif(10)) So first just do it for a cubic: > mmn = lmn(d,3) > predict(mmn[[3]]) 1 2 3 4 5 6 7 8

data from multilevel units,first sample the class ,and then the student in calss.following is the 2-level model. and the level-1 model deals with the student,and the level-2 model deals with the class level the students belong to. Level-1 Model Y = B0 + B1*(ZLEAD) + B2*(ZBUL) + B3*(ZSHY) + R Level-2 Model B0 = G00 + U0 B1 = G10 + G11*(ZWARMT) + U1 B2 = G20 + G21*(ZWARMT) + G22*(ZABLET) +

Hello everyone, I have two problems which I am unable to solve : 1.I am trying to add the  row labels (g1-g2000) to the very left of a data table. The data table is 2000 rows  by 62 columns.I have used the following code. read.table(file="C:\\Documents and Settings\\Owner\\My Documents\\colon cancer1.txt",header=T,row.names=1) rowname(dat) <- paste("g", c(1:nrow(dat)),

Hey list! It looks simple, though it's not possible for me to plot the following properly: (some made-up data) GrSe Clone1 Clone2 Clone3 Clone4 Clone... G1999 2 3 6 5 G2000 2 5 7 4 G2001 5 3 7 3 G2002 4 5 8 3 G... GrSe=Growing Season. I've read the file as "x" and then tried: plot(x$GrSe,x$Clone1) The output is 4 horizontal bars. Even if I write

I'm trying to sort a DATAFRAME by a column "ID" that contains alphanumeric data. Specifically,"ID" contains integers all preceeded by the character "g" as in: g1, g6, g3, g19, g100, g2, g39 I am using the following code: DATAFRAME=DATAFRAME[order(DATAFRAME1$ID),] and was hoping it would sort the dataframe by ID in the following manner g1, g2, g3, g6, g19,

Dear All, Need some help in polynomials transformation to get the coefficients. I have tried "poly.transform" as applied in S-plus but it does not work. Thanks in advanced for any helps. Regards. Abd. Rahman Kassim (PhD) Head Forest Ecology Branch Forest Management & Ecology Program Forestry and Conservation Division Forest Research Institute Malaysia Kepong 52109 Selangor,