similar to: help about R basic

Read the data using scan(): # # a1 a2 a3 a4 # ------------- ------------- ------------- ------------- # b1 b2 b3 b1 b2 b3 b1 b2 b3 b1 b2 b3 # --- --- --- --- --- --- --- --- --- --- --- --- # # c1: # 4.1 4.6 3.7 4.9 5.2 4.7 5.0 6.1 5.5 3.9 4.4 3.7 # 4.3 4.9

Hi, May be this helps: m1<- as.matrix(read.table(text=" y1 g24 y1 0 1 g24 1 0 ",sep="",header=TRUE)) m2<-as.matrix(read.table(text="y1 c1 c2 l17 ?y1 0 1 1 1 ?c1 1 0 1 1 ?c2 1 1 0 1 ?l17 1 1 1 0",sep="",header=TRUE)) m3<- as.matrix(read.table(text="y1 h4??? s2???? s30 ?y1 0 1 1 1 ?h4 1 0 1 1 ?s2 1 1 0 1 ?s30 1 1 1

I have a dataset that is basically structureless. Its dimension varies from row to row and sep(s) are a mixture of tab and semi colon (;) and example is HEADER1 HEADER2 HEADER3 HEADER3 A1 B1 C1 X11;X12;X13 A2 B2 C2 X21;X22;X23;X24;X25 A3 B3 C3 A4 B4 C4 X41;X42;X43 A5 B5 C5 X51 etc., say. Note that a blank

These are supported on GK20A and GM107. Signed-off-by: Ilia Mirkin <imirkin at alum.mit.edu> --- Was a bit torn on where to place the enums... we're about to gut all the xml definitions so this seemed appropriate for now. Tested on GK20A only. src/gallium/drivers/nouveau/nv50/nv50_formats.c | 64 +++++++++++++++++++++++++ src/gallium/drivers/nouveau/nvc0/nvc0_screen.c | 10 ++++

Why not fix the new names instead to be like the old names? Seems like that would be way simpler... On Feb 15, 2016 12:38 AM, "Ben Skeggs" <skeggsb at gmail.com> wrote: > From: Ben Skeggs <bskeggs at redhat.com> > > We've previously had identical naming between vertex and texture > formats, so it mostly made sense to define these together. > > However,

Hi! I am a bit new to R. I am looking for the right function to use for a multiple regression problem of the form: y = c1 + x1 + (c2 * x2) - (c3 * x3) Where c1, c2, and c3 are the desired regression coefficients that are subject to the following constraints: 0.0 < c2 < 1.0, and 0.0 < c3 < 1.0 y, x1, x2, and x3 are observed data. I have a total of 6 rows of data in a data set. Is

Hi, I observed below behavior with Instruction combiner (visitMul Canonicalization) It tries to convert "(X+C1)*C2" to "X*C2+C1*C2" While transforming if operation is guaranteed to not overflow it does not reflect same property to transformed instructions. Consider following scenarios: 1) If input is ((X+C1)*C2)<nsw> Then post canonicalization output should be

This message is in MIME format. The first part should be readable text, while the remaining parts are likely unreadable without MIME-aware tools. Send mail to mime@docserver.cac.washington.edu for more info. ---559023410-1251336619-945861747=:5357 Content-Type: TEXT/PLAIN; charset=US-ASCII While fiddling with apply I noticed that there appears to be an error in the dimnames, which actually

Dear professor Fox and R helpers, I have a quick question about the Anova function in the car package. When using the default "type II" SS I get results that I don't understand (see below). library(car) Data <- data.frame(y=rnorm(10), x1=factor(c(rep("a",4), rep("b",6))), x2 = factor(c(rep("j", 2), rep("k", 3), rep("j", 2),

Hi suppose I have two arrays x1,x2 of dimensions a1,b1,c1 and a2,b2,c2 respectively. I want x = x1 "+" x2 with dimensions c(max(a1,a2), max(b1,b2),max (c1,c2)) with x[a,b,c] = x1[a1,b1,c1] + x2[a2,b2,c2] if a <=min(a1,a2) , b<=min (b1,b2), c<=min(c1,c2) and the other bits either x1 or x2 or zero according to whether the coordinates are "in range" for

My data frame consists of character variables, factors, and proportions, something like c1 <- c("A", "B", "C", "C") c2 <- factor(c(1, 1, 2, 2), labels = c("Y","N")) x <- c(0.5234, 0.6919, 0.2307, 0.1160) y <- c(0.9251, 0.7616, 0.3624, 0.4462) df <- data.frame(c1, c2, x, y) pct <- function(x) round(100*x, 1) I want to

Hi, I have a data frame where one column is a list of lists. I would like to subset the data frame based on membership of the lists in that column and be able to 'denormalise' the data frame so that a row is duplicated for each of its list elements. Example code follows: # The data is read in in this form with the c2 list values in single strings which I then split to give lists: > f1

Dear R-users, For a data frame (say in this example X) I want to look up the corresponding value in a 'look-up data frame' (in this example Y). The for-loop works but is very time-consuming because 'X' in reality is very big. Therefore I would like to have a solution with apply. However, I do not succeed. Any suggestions? Thanks in advance, Hanneke

Hello, I am relatively new to R, and I am trying to select the last observation within a group, where the group is defined by two variables. One of the variables is a date. In the below example, C3 varies within C2, which varies within C1. I need to select the last observation in C3 for 4 groups (C1*C2): 1x, 1y, 2x, and 2y. In my real dataset, C2 is a date (mm/dd/yy) C1 C2 C3 1 x 1 1

can list names attributes be preserved through S4 class containment? seems to be so but only if the containment relationship is direct ... see below. > setClass("c1", contains="list") [1] "c1" > l1 = list(a=1, b=2) > o1 = new("c1", l1) > names(o1) # pleasant surprise [1] "a" "b" > setClass("c2",

## Hi, I'm having trouble understanding how the cbind function decides what method to apply to its arguments. Easy cut and paste code below. > > > > ## create two columns > c1 <- c("A","A","B","B") > c2 <- 1:4 > > ## cbind outputs a matrix with elements that are characters, seems reasonable > out <-

hello gurus, i have a data frame like this HTN HTN_FDR Dyslipidemia CAD t1d_ptype[1:25] 1 Y Y Y T1D 2 T1D 3 Ctrl_FDR 4 T1D 5 Y Ctrl 6 Ctrl 7

Hi there, I am trying to use linear regression to solve the following equation - y <- c(0.2525, 0.3448, 0.2358, 0.3696, 0.2708, 0.1667, 0.2941, 0.2333, 0.1500, 0.3077, 0.3462, 0.1667, 0.2500, 0.3214, 0.1364) x2 <- c(0.368, 0.537, 0.379, 0.472, 0.401, 0.361, 0.644, 0.444, 0.440, 0.676, 0.679, 0.622, 0.450, 0.379, 0.620) x1 <- 1-x2 # equation lmFit <- lm(y ~ x1 + x2) lmFit Call:

Hi, I'm trying to match peaks between chromatographic runs. I'm able to match peaks when they are chromatographed with the same method, but not when there are different methods are used and spectra comes in to play. While searching I found the ALS package which should be usefull for my application, but I couldn't figure it out. I made some dummy chroms with R, which mimic my actual

R experts, I have three columns. c1 and c2 are numeric variables whereas c3 are the clusters classes (nominal variable, 10 different: cluster1, cluster2, cluster3, cluster4, cluster5 ....). I'd like to plot c1 against c2 (easy!) in a 2D plot and put different color depending to the cluster class automatically regardless the number of clusters. Could anyone give a hand? Josep Maria, matrix