similar to: Rearranging Data

Dear all I have found that the two "equivalent" commands do not produce the same results. 1. (I wrote this command by hand, this is what I would do usually) >summary(aov(eduyrs ~ cntry * edf, data=ESS1)) Df Sum Sq Mean Sq F value Pr(>F) cntry 1 257 256.65 21.2251 4.243e-06 *** edf 4 11010 2752.42 227.6296 <

Hello all, I hope something is not already posted regarding this exact problem I am trying to solve. I've read through the forums and previous postings and am still confused as to how to approach this. Basically, what I am trying to do is construct variables that utilizes an average of a variable from a grouping, or higher order, variable. For instance, in my dataset I have variables, with

Muchas gracias. Me puede recomendar algún libro donde poder empezar. Gracias El 18/06/2017 9:46 p. m., <javier.ruben.marcuzzi en gmail.com> escribió: > > > Estimado Antonio Rodriguez Andres > > > > Usted dice que está en sus inicios con R, y desea realizar un gráfico. > Esto no es problema, el inconveniente es que está mezclando librerías, es > lógico, se puede

Estimados Soy un nuevo usario de R, y estoy usando como base de datos el European Social Survey, que tiene datos de 40,000 individuos, y alrededor de 23 países europeos. Lo que he seleccionado es la útima ola, el round 7, para el año 2014. He leido los datos, desde SPSS y aquí tienen la base de datos y que tipo de objetos se han generado, y tambíen la distribución por pais de la muestra. No he

Creo que esto me da para DK, y luego veré como aplicar el barplot ess %>% filter(cntry %in% c("DK")) %>% count (stflife) %>% mutate (freq = (n /sum(n)*100))%>% print 2017-06-18 19:01 GMT-05:00 Antonio Rodriguez Andres < antoniorodriguezandres70 en gmail.com>: > He conseguido el total para un país, pero no me deja usar percent = > count() /sum(count),

I have cobbled together the following logic. It works but is very slow. I'm sure that there must be a better r-specific way to implement this kind of thing, but have been unable to find/understand one. Any help would be appreciated. hh.sub <- households[c("HOUSEID","HHFAMINC")] for (indx in 1:length(hh.sub$HOUSEID)) { if ((hh.sub$HHFAMINC[indx] == '01')

Dear colleagues: Despite my best efforts, I have not been able to understand/overcome an error message I received while running the fclustIndex command in package e1071, which produces validity measures for the fuzzy c-means clustering algorithm. I am relatively new to R-- and still depend heavily on Rcmdr-- and so I apologize in advance if there is an obvious answer to my question:

#Simple table con frecuencias absolutas y crear relativas count =table(ess$stflife) percent = 100* (count)/sum(count) Carlos he creado a esto a nivel general en vez de usar prop.table. Según lo que dices o entiendo, debo de usar la función ddply para hacerlo a nivel de todos los paises, y entiendo que ddply (, c(""), debo de indicar los paises? Saludos 2017-06-18 17:37 GMT-05:00

Gracias. Alguna idea de que usar para calcular los porcentajes y almacenarlos. Se puede usar flat table? El 18/06/2017 4:50 p. m., "Carlos J. Gil Bellosta" <cgb en datanalytics.com> escribió: > Los porcentajes que obtienes con tu código son sobre todas las facetas, no > país a país. > > Calcula los porcentajes previamente a por país y representa esa columna en >

I believe I have found the cause of the unexplained error (code ??) at main.c(line #). In the version I'm running 2.5.2 (obtained from the Free Software Foundation) the line number is 576. It appears the root cause is related to a race condition associated with the termination of child processes. If the signal handler for SIGCHILD is executed, as the result of a child termination, before the

Hola! I am programming a class (S3) "symarray" for storing the results of functions symmetric in its k arguments. Intended use is for association indices for more than two variables, for instance coresistivity against antibiotics. There is one programming problem I haven't solved, making an inverse of the index function indx() --- se code below. It could for instance return the

> Hello, > > Is this the fastest way to use indices from one matrix to reference rows > in another smaller matrix? I am dealing with very big data (lots of columns > and I have to do this lots of times). > > ######sample data ############## > vals = matrix(LETTERS[1:9], nrow=3,ncol=3) > colnames(vals) = c('col1','col2','col3') > rownames(vals)

I found a bug in one of the fourteen speed patches I posted, namely in patch-vec-subset. I've fixed this (I now see one does need to duplicate index vectors sometimes, though one can avoid it most of the time). I also split this patch in two, since it really has two different and independent parts. The patch-vec-subset patch now has only some straightforward (locally-checkable) speedups for

Looking at shash in unique.c, from R-2.10.1 I'm wondering if it makes sense to hash the pointer itself rather than the string it points to? In other words could the SEXP pointer be cast to unsigned int and the usual scatter be called on that as if it were integer? shash would look like a slightly modified version of ihash like this : static int shash(SEXP x, int indx, HashData *d) {

Folks: In answer to a query, Andy Liaw recently submitted some code to construct a block diagonal matrix. For what seemed a fairly straightforward task, the code seemed a little "overweight" to me (that's an American stock analyst's term, btw), so I came up with a slightly cleaner version (with help from Andy): bdiag<-function(...){ mlist<-list(...) ## handle case in

Dear All, I would like to ask you help with the following: Assume that I have an area of 36 cells (or sub-areas) sr<-matrix(data=seq(from=1,to=36),nrow=6,ncol=6,byrow=TRUE) > sr [,1] [,2] [,3] [,4] [,5] [,6] [1,] 1 2 3 4 5 6 [2,] 7 8 9 10 11 12 [3,] 13 14 15 16 17 18 [4,] 19 20 21 22 23 24 [5,] 25 26 27 28 29 30 [6,]

Hi guys, i'm not going to have time to work on this for a month or two, so i figured i'd post it. This patch 1. reworks the andersen's implementation to support field sensitivity (though field-sensitive constraints are not generated directly yet), and uses it to do indirect function call support. 2. Rewrites the solver to be state of the art in terms of speed. kimwitu++ used to take

Hello all, I posted the following bug last week: # These calls work correctly: match(c("A", "B", "C"), c("A","C"), incomparables=NA) # okay match(c("A", "B", "C"), "A") # okay match("A", c("A", "B"), incomparables=NA) # okay # This one causes R to hang: match(c("A",

Hi, It would be better if you provided the output of dput(dataset).? I am not sure about the structure of your dataset. Just from reading the data as is shown. dat1<- read.table(text=" separator,tissID >,>,2 ,2,1 ,6,5 ,11,13 >,>,4 ,4,9 ,6,2 ,7,3 ,21,1 ,23,58 ,25,9 ,26,4 >,>,11 ,1,12 >,>,21 ,4,1 ,11,3

Full_Name: Vilmos Prokaj Version: R 2.7.1 OS: windows Submission from: (NULL) (213.181.195.84) Dear developers, The following line of code (produced by a mistake) caused an infinite loop unique("a",c("a","b")) or also unique(1,1:2) I made a little investigation, and it seems to be that the following function from unique.c is looping infinitely static int