similar to: Converting a line by line program into an array to perform summary stats

Hello, I wrote this code which works fine on a single observation: x<-100 y<-200 z<-125 aa<-150 if(x<z && y>z) {aa-z} result: 25 I am trying to apply this logic where x,y,z,and aa are arrays but with very little success. I have tried using loops and whiles but I always get errors of various types. I have consulted a few manuals but with limited success. My hopeful

I''m using the fields_for helper with accepts_nested_attributes_for The System model has_many children. If I do this in my haml template: -form_for @system do |s| =s.text_field :name -s.fields_for :children do |child_fields| =child_fields.text_field :name all is fine. The fields_for iterates over all children and puts the correct data in the fields. But...what I

Hello, I am trying to find a direct way to write a nested if of sorts to find data for a specific time range for a specific day (across a range of days) and have exhausted my abilities with the manuals I have at hand. I have a good deal of data of this approximate form: day time price 1 1am 5 1 2am 7 1 3am 9 1 4am 12 2 1am 5 2 2am 7 2

where to fidn the rpm package

Konqueror crashes reqularly and I would like to reinstall it. How do I reinstall KDE and/or Konqueror? -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://lists.centos.org/pipermail/centos/attachments/20051201/a0acf8fd/attachment-0002.html>

When trying to connect to my USBDISK I receive an error message that it is not supported. -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://lists.centos.org/pipermail/centos/attachments/20051201/4d4afd84/attachment-0002.html>

Suppose I have data like this: A <- sample(letters[1:3], 1000, replace=TRUE) B <- sample(LETTERS[1:2], 1000, replace=TRUE) x <- rnorm(1000) I can get a table of means via tapply(x, list(A, B), mean) and I can add the marginal means to this using cbind/rbind: main <- tapply(x, list(A,B), mean) Amargin <- tapply(x, list(A), mean) Bmargin <- tapply(x, list(B), mean)

I'm sorry for what I'm sure is a terribly simple question. I have a large dataframe along these lines: S<- 1:3 d<- data.frame(cbind(S=rep(paste('S',S,sep=""),each=30), trial=rep(1:3,each=10), FactorA=rep(paste('L',1,sep=""),each=30), Acc= c(rep(1,each=20),rep(0,each=10)), Sample=rep(1:10,3), DV= sample(runif(10),10))) but where each

I'm looking for a function that lists a few summary stats for a column (or row) of data. I'm aware of summary(x), but that does not give me what I'm looking for. I'm actually looking for something that is very similar to the descriptive statistics tool in excel; i.e. Mean, Std. Error, Std. Deviation, Kurtosis. I'm positive that I came across a function that did this (possibly

I have a data set that has student test scores along with several categorical variables. I would like to generate a set of summary stats (mean, variance, n) for the data grouped by school authority and by exam topic. I have tried the by() function but that seems to only be able to handle one level of grouping. In particular what I would like is something like the following Board Subject Mean

List, I am trying to extract summary statistics from a data frame with several variables (and NAs) into a dataframe with the columns: Variablename (ie the colnames of original data), mean, stdev, max, min, Valid N, Missing Values. Extracting the statistics is straightforward using stack and aggregate. However, I haven''t succeeded in obtaining the number of Missing Values. I can extract

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Dear List, I am looking to run a host of models (60) with three methods - lmer,glm and lrm. Is there a way to output the key stats into a table that i can copy to excel? I.e for lmer i would want AIC,BIC etc for lrm i would want Brier score, r2, c-value etc At present i am running the models from a script and then copying across the values into a excel spreadsheet however this is time

Hello, I have the following data.frame structure(list(Study = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L,

Given a matrix of m*n, I want to reorder it as a vector, using a row major transpose. so: > m<-matrix(seq(1,48),nrow=6,byrow=T) > m [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [1,] 1 2 3 4 5 6 7 8 [2,] 9 10 11 12 13 14 15 16 [3,] 17 18 19 20 21 22 23 24 [4,] 25 26 27 28 29 30 31 32 [5,] 33 34 35 36 37

Hey Nithya, root at PB-WA-AA-00-A:/# glusterfs -V glusterfs 3.10.1 Repository revision: git://git.gluster.org/glusterfs.git Copyright (c) 2006-2016 Red Hat, Inc. <https://www.gluster.org/> GlusterFS comes with ABSOLUTELY NO WARRANTY. It is licensed to you under your choice of the GNU Lesser General Public License, version 3 or any later version (LGPLv3 or later), or the GNU General Public

I am really getting into my new Ubuntu Hardy Heron software but wondered if any music lovers amongst you could give me some advice? I heavily use Band in a Box 2008 on the XP side of my machine and have tried to install it, through the wine emulator so I can use it in Ubuntu. I could then, more or less, abandon the XP side on a 90% basic. Something I would very much like to do. Unfortunately BB

Several questions really (all on the stable 2.2.2 samba compiled with winbind and acls (and Brandon Stone's recycle bin), with a 2.4.14 kernel along with acls from acl.bestbits.at on a RedHat 7.2 box)... 1) Does anyone know how to stop the security event log on an NT PDC filling up with lots of ANONYMOUS accesses to the Security Account Manager eg: Object Open: Object Server: Security

Hi! Can anyone tell me how to convert the anova/ancova summary output into a data frame? Thanks! Shane Phillips [[alternative HTML version deleted]]

Hi, I am trying to convert a dataset (dataframe) into time series object using ts function in stats package. My dataset is as follows: >df [1] 11.08 7.08 7.08 6.08 6.08 6.08 23.08 32.08 8.08 11.08 6.08 13.08 13.83 16.83 19.83 8.83 20.83 17.83 [19] 9.83 20.83 10.83 12.83 15.83 11.83 I converted this into time series object as follows >tsdata <-