similar to: transform a table into a matrix

Dear fellow R users, I am now investing time in learning how to use compiled C code to produces functions that can be used in R. I am just starting, and there is much that I need to learn, so I have a question that might be straight forward. I am learning how to use function in the C library GSL (gnu scientific library), to write C code, that I then plant to use in R. Is there any problem in

Does anyone know of a literature reference, or a piece of code that can help me calculate the amount of variation explained (R2 value), in a regression constrained to have a slope of 1 and an intercept of 0? Thanks! Sebastian J. Sebastián Tello Department of Biological Sciences 285 Life Sciences Building Louisiana State University Baton Rouge, LA, 70803 (225) 578-4284 (office and lab.)

Dear R-List, My questions concerns missing values. Specifically, is is possible to use different "types" of missingness in a dataset and not a one-size-fits-all NA? For example, data may be missing because of an outright refusal by a respondent to answer a question, or because she didn't know an answer, or because the item simply did not apply. In later analysis it is sometimes

I have a data.frame as follows: a 3 a 2 a 1 b 3 b 2 c 2 c 3 c 1 c 1 Each factor (a, b, c) should be monotonically decreasing, notice that factor 'c' is not. I could use some help to figure out how to form a logical structure (mostly just syntax), that will check each 'next value' for each factor to see if it is less than the previous value. If it is less than the

Hi everyone- I have used several methods to calculate principal components rotated using the varimax procedure. This is simple enough. But I would like to calculate the % of variance explained associated with each PC before and after rotation. factanal returns the % of variance explained associated with each PC but I cannot seem to get it to change after rotation. Many thanks for your

Hello everyone- I have a 3-d array with the 1st dimension being monthly mean data that I would like to correlate with some time series index, for example, and save the coefficients in an array. The code I am currently running is.... rData <- array(0,c(73,144)) # array to store results for (i in 1:73) { for (j in 1:144) { rData[i,j] <- cor(slp[,i,j],y)

Dear all, I have been using the function gls in the package nlme in R to fit some spatial regressions (as described in Dormann et al.). However, I have been struggling trying to find a way to calculate a measure of effect size from these models, so I wanted to know if any of you had an idea on how to do this. More precisely, I am producing a multiple model with an exponential correlation

Dear R Listers- I am attempting to analyse the survival of seeds in cages (exclosures) that differ in their permeability to rainforest mammals. Because I did not observe the moment of seed disappearance, my data is interval censored. This limits my options for analysis (as I understand it) to survreg, in the survival package. Because I repeated the experiment in 8 sites, I have a random

Dear R Gurus - Please help me to make a multiple-panel plot using xYplot in which the y-axis of each panel is dependent only on the data of that plot. Here is the dataset: response date mean Lower Upper 1 density 1 271.0000000 249.2500000 289.0000000 2 density 4 296.7500000 280.5000000 313.0000000 3 recruits 1 271.0000000 249.2500000

Hello R-listers, I am using xtable to create some LaTeX tables for me to Sweave into my document. I am now trying to set the number of digits that will be reported in several _rows_ in my table. The 'digits' option in xtable() sets the number of digits to display for specified columns. Am I missing another obvious option to do the same thing for rows? A quick RSiteSearch didn't turn

Dear R users, I am looking for more efficient way to compute the followings -------------------------------------------------------------------------- a <- matrix(c(1,1,1,1,2,2,2,2),4,2) b <- matrix(c(1,2,3,4),4,1) Eventually, I want to get this matrix, `c`. c <- matrix(c(1/1,1/2,1/3,1/4,2/1,2/2,2/3,2/4),4,2) --------------------------------------------------------------------------

Dear list, I have two vectors: x <- c("one","two") y <- paste(rep(x,2),"blah") I want to replace all occurrences of each element of x in y with something else, so that y looks like this: y [1] "something else blah" "something else blah" "something else blah" [4] "something else blah" I can do this using a loop: for (

Hello Hello I have a data frame, x, holding 5 persons answering the question which cars they have used: # the data frame x <- as.data.frame( matrix( c('BMW', '', '', 'Mercedes', 'VW', '', 'Skoda', 'VW', 'BMW', '', '', '', 'VW', 'Skoda',

I have a really long functions, and at the end of the function, I am using a if statement to tag certain keywords based on whether they have certain values contained in them. However, the if statement doesn't seem to work. When I had split up the commands into various functions, it worked fine, but I'm not sure what going on now that it's combined into a single function. myfunc

Hello again- Thanks to Prof. Ripley for responding to my previous question. I would like to clarify my question using sample code. I will use some sample code taken from ?prcomp Again, I would like to compare the % variance explained by each PC before and after rotation. < code follows > data(USArrests) pca = prcomp(USArrests, scale = TRUE) # proportion variance explained by each

Greetings all. Any help with the following would be appreciated. I want to create a data frame for each file in a directory. The following code does not work but it may show what I am trying to do: carmakes <- c('BMW','Chrysler','Citroen','Fiat','Ford','Holden','Honda',

On Tue, 30 May 2023 17:43:31 +0000 Heather Lucas <hlucas2 at lsu.edu> wrote: > Hello, > > I've been enjoying using the "Mixture and Hidden Markov Models in R" > by Visser & Speekenbrink to learn how to apply these analyses to my > own data using depmixS4. > > I currently have a fitted 4-state mixture model with three emissions > variables and one

Ahh yes, sorry about that. Here's the corrected snippet: # Create an Example Data Frame Containing Car x Color data carnames <- c("bmw","renault","mercedes","seat") carcolors <- c("red","white","silver","green") datavals <- round(rnorm(16, mean=10, sd=4),1) data <- data.frame(Car=rep(carnames,4),

Hi I have some data that i want to plot but i don't find how to do it. I have car types (bmw,renault,mercedes,seat ...), colors and a number for each car type-color relation.I want to come up with a matrix representation of cars vs colors where in each intersection i could set a dot proportional in size to my third variable. Can anybody give me a clue of hoe to come up with such

Muchas gracias Carlos, Me da error al hacerlo. Mi variable donde quiero que localice las palabras de la lista tiene más de una palabra, no se si puede ser por eso. Gracias El Mar, 22 de Mayo de 2018, 20:15, Carlos Ortega escribió: > Hola, > > Aquí tienes un ejemplo (reproducible)... > > #----------------------- >> # Generar nombres de mujer >> library(randNames)