similar to: Formatting Syntax when Merging

Hi everyone, I'm trying to break down data into intervals because I need to analyze data according to the intervals between each change in value. What I have done is merged the attached data files, and filled in the missing values this way: > fmt<-"%m/%d/%y" > dd<-read.csv("Desktop/R/CDSdate.txt") > dd$Date<-as.Date(dd$Date, fmt) >library(zoo)

Hi: I need some help. I am ploting a bar graph but I can't adjust my x axis scale I use this code: i <- qplot(ForkLength,Number,data=FL,geom="bar") i + geom_bar(colour="blue",fill="grey65") # too crowded FL_dat <- ggplot(FL,aes(x=ForkLength,y=Number)) + geom_bar(colour="green",fill="grey65") FL_dat +

Hi list-members can anybody tell me why > pairwise.t.test(val, fac) produces an empty p-table. As shown below: Pairwise comparisons using t tests with pooled SD data: val and fac AS AT Fhh Fm Fmk Fmu GBS Gf HFS Hn jAL Kol R_Fill AT - - - - - - - - - - - - - Fhh - - - - - - - - - - - - - Fm - - - - - - -

Hi, I am trying to plot the Case-Shiller index found at: http://www2.standardandpoors.com/spf/pdf/index/CSHomePrice_History_022445.xls The way I'm importing it into R is as follows: library(gdata) W <- read.xls("http://www2.standardandpoors.com/spf/pdf/index/CSHomePrice_History_022445.xls ", header=TRUE) attach(W) To give you and idea of what the data looks like: >

Hi All, I need to parse data from a file, example shown below. The first two lines can be skipped, the third line contains the column names. The next 13 lines can be skipped. The next line "1991" is a year value, with the following 13 values data for that year. The file then repeats this format with (year, 13 lines of data for that year). I would ideally like to end up with an

Dear group, Here is my df : pose16 <- structure(list(DESCRIPTION = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 12L), .Label = c("COPPER May/10", "COTTON NO.2 Jul/10", "CRUDE OIL miNY May/10", "GOLD Jun/10", "ROBUSTA COFFEE (10) Jul/10", "SOYBEANS Jul/10", "SUGAR NO.11 Jul/10", "SUGAR NO.11 May/10",

Hi, I have a question on generating random variables based on zipf-mandelbrot distribution. So when I execute the following lines: ZM = lnre ("zm", alpha = 2/3, B=0.1) zmsample = rlnre (ZM, n =100) zmsample It generates 100 random values based on a zipf-mandelbrot distribution as below. But how do I make sure the generated random number is within the range of 1 - 6000 only? Can I

Dear group, I have 3 data frames I would like to merge. Here they are: pose16 <- structure(list(DESCRIPTION = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 12L), .Label = c("COPPER May/10", "COTTON NO.2 Jul/10", "CRUDE OIL miNY May/10", "GOLD Jun/10", "ROBUSTA COFFEE (10) Jul/10", "SOYBEANS Jul/10", "SUGAR NO.11

Dear all I am a BEGINNER and have R on my Mac. I saved my excel file as .txt file, I have just one column with first row as the column name. My file when read by R looks like this. After reading the table I try to make a histogram by hist(dbh), it says object dbh not found. What am I doing wrong? thanks dbh 1 11.53 2 16.05 3 7.36 4 16.05 5 8.66 6 12.74 7 22.93 8 7.55 9

Hi How would I analyse time series with - different lengths (i.e. one has 9 entries and the other has 14 entries) - different frequency (i.e. dates are random - no repeated length) - multiple values for the same time entry (e.g. 2009-10-23 below) i.e. my data takes the form: 1st time series 2009-10-07 0.009378 2009-10-19 0.014790 2009-10-23 -0.005946 2009-10-23 0.009096 2009-11-08 0.004189

Hello, It's an alternative to use SAS by function in R? I want to plot d histograms by plot.from example bellow: Thank you! plot d 1 1 16.3 2 1 25.0 3 1 57.8 4 1 17.0 5 2 10.8 13 2 96.4 17 3 76.0 18 3 32.0 19 3 11.0 20 3 11.0 24 3 106.0 25 3 12.5 21 4 19.3 22 4 12.0 26 4 15.0 27 5 99.3 32 7 11.0 36

I tried toy problems and there doesn't seem to be a basic problem between lm() and ts objects: X = data.frame(x=c(1,2,7,9), y=c(7,2,3,1)) lm(y ~ x, X) X <- lapply(X, function(x) ts(x, frequency=12, start=c(1994,7))) lm(y ~ x, X) and this works fine - whether you do an lm() before or after making ts objects, it's okay. But I have a situation where things aren't okay.

Dear Community, I have been using two types of survival programs to analyse a data set. The first one is an R function called aftreg. The second one an STATA function called streg. Both of them include the same analyisis with a weibull distribution. Yet, results are very different. Shouldn't the results be the same? Kind regards, J -- View this message in context:

Hello, dear R-community. This is a question about TukeyHSD between factor combinations of a Three-Way ANOVA, which is - since it is a multi measure ANOVA - not a simple ANOVA but a Generalised Linear Mixed Model (GLMM), calculated with "lmer". > growth <- groupedData(length~meas|box_id,outer=~spec*comp*water,data=all.spec) > model <-

Hi, I want to use the first digit of the elements of a vector. I've tried grep but didn't work. Any help is welcome. Thanks EJ > grep("^[0-9]",as.character(runif(100,0,2))) [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 [19] 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 [37] 37 38 39 40 41 42 43 44 45

Hi All, I have a sample of data set show as below. tdat <- read.table(textConnection("stat year Y AL 2003 25 AL 2003 13 AL 2004 21 AL 2006 20 AL 2007 12 AL 2009 16 AL 2010 15 FL 2006 63 FL 2007 14 FL 2007 25 FL 2009 64 FL 2009 47 FL 2010 48 NY 2003 50 NY 2004 51 NY 2006 57 NY 2007 62 NY 2007 36 NY 2009 87 NY 2009 96 NY 2010

_History_ I have 100% success in Xen VGA Passthrough with Xen 3.5-unstable with my first Palit NVIDIA Geforce 8400 GS VGA card in 2009, which is 3 years ago. Then my first Palit NVIDIA Geforce 8400 GS VGA card overheated and malfunctioned. So I bought a 2nd Palit NVIDIA Geforce 8400 GS VGA card several months ago in March 2012 for S$44, to replace the first card. At that point in time, Xen

_History_ I have 100% success in Xen VGA Passthrough with Xen 3.5-unstable with my first Palit NVIDIA Geforce 8400 GS VGA card in 2009, which is 3 years ago. Then my first Palit NVIDIA Geforce 8400 GS VGA card overheated and malfunctioned. So I bought a 2nd Palit NVIDIA Geforce 8400 GS VGA card several months ago in March 2012 for S$44, to replace the first card. At that point in time, Xen

  I want to input a list into a function. But i get the error "Error in +{ : invalid argument to unary operator". How do I avoid this error?   Here is an example of this problem:   > g = c(2, 4, 8, 16, 32, 64, 128, 122, 110, 86, 38, 76, 18, 36, 72, 10, 20, 40, 80, 26) > for (i in 1:20)  + {for (x in 0:20)  + print(g[i]+x)} [1] 2 [1] 3 [1] 4 [1] 5 [1] 6 [1] 7 [1] 8 [1] 9 [1] 10

Hi All, Except the "Rand Index", "Dunn Index" and "Silhouette width", are there other cluster validation methods in R? Could you please also specify the function? Thanks! [[alternative HTML version deleted]]