similar to: Sorting Panel Data by Time

# I have a dataframe in the following form: track <- c(rep('A', 3), rep('B', 4), rep('C', 4)) value <- c(0.15, 0.25, 0.35, 0.05, 0.99, 0.32, 0.13, 0.80, 0.75, 0.60, 0.44) df <- data.frame(track=factor(track), value=value) #> print(df) #track value #1 A 0.15 #2 A 0.25 #3 A 0.35 #4 B 0.05 #5 B 0.99 #6 B 0.32 #7 B 0.13

I try to utilize some operations on rows in a matrix using command 'apply' but find a problem. First I write a simple function to normalize a vector (ignore error handling) as follows: normalize = function( v ) { return( ( v-min(v) ) / ( max(v) - min(v) ) ) } The function works fine for a vector: > normalize( 1:5 ) [1] 0.00 0.25 0.50 0.75 1.00 Then I generate a matrix: > a =

Hi, I'm stuck on creating a plot with x tick labels for every Nth tick mark - how is that done? I don't see a simple solution to this in help(plot) or help(par) and what I've tried is not working, eg, the following does not work, although it seems intuitive to me that it should work: x <- seq(-100,1000,25) y <- x * x % find all the x values that are multiples of 100 tmp <-

Hi, i am new to this forum and not sure how it works, I am trying to do deskriptive descripe my data in terms of gender: head(scltotal) pbnr dat dep dys sop ago mis age female messpunkt2 messpunkt1 tage eintrittsjahr 1 10023 1994-02-21 0.75 1.00 0.50 0.50 0.75 35 1 8817 8817 0 1994 2 10023 1994-05-25 0.75 1.00 0.50 0.50 0.75 35 1 8910 8817

Dear list I'm testing a predictor and I produced nice performance plots with ROCR package utilizing the 3 standard command pred <- prediction(predictions, labels) perf <- performance(pred, measure = "tpr", x.measure = "fpr") plot(perf, col=rainbow(10)) The pred object and the perfo object are S4 with the following slots An object of class "performance"

Dear list, I have observed a weird behaviour from R --- apologies if I am missing something obvious! df3f826f28 df3f826f28 Say you type in R: >c.preec <- 10074 >c.gd <- 2200 >p1 <- .2 >c.neo <- p1*9451 + (1-p1)*3883 >n.preec <- 3710 >n.gd <- 2650 >n.neo <- 2120 >n.pcos <- 53000 >unit.met <- 94 >cost.met <- 94*n.pcos >effect <-

Hola a todos, Estoy usando la librería ltm, de teoría de respuesta al ítem, para crear gráficos. Resulta que añado unas líneas horizontales en los valores de 0.25, 0.50 y 0.75. Me gustaría que en el gráfico, desaparezcan las marcas de 0,.2, 0.4, 0.6 y 0.8 y aparezcan en 0.25, 0.50 y 0.75. He probado varias cosas que he visto por Googe pero no me han funcionado. ¿Alguna idea? library(ltm) # creo el

I start a clean session of R 1.9.1 on Windows and I run the following code: > library(MASS) > data(painters) > pca.painters <- princomp(painters[ ,1:4]) > loadings(pca.painters) Loadings: Comp.1 Comp.2 Comp.3 Comp.4 Composition 0.484 -0.376 0.784 -0.101 Drawing 0.424 0.187 -0.280 -0.841 Colour -0.381 -0.845 -0.211 -0.310 Expression 0.664 -0.330 -0.513

Hi all, This seems like a basic problem, but no amount of playing with the code has solved it. I have a time-series data set like that shown below (only longer) and am seeking to plot the data with filled, circular points and error bars. I would like the error bars to be behind the points otherwise they tend to obscure the points (especially when I have a lot of points in the actual data set).

Hi, I'm trying to create a distance matrix. And it works out somewhat ok. However, I suspect that there are some efficiency issues with my efforts. Plz have a look at this: donor <- matrix(c(3,1,2,3,3,1,4,3,5,1,3,2), ncol=4) receiver <- matrix(c(1,4,3,2,4,3,1,5,1,3,2,1,4,5,3,5,1,3,2,4,5,1,2,3,1,4,5,5,1,2,1,3,4,3,2,5,5,1,4,2,5,4,3,2), ncol=4) The above creates my two matrices. I have

Greetings.? My wife is teaching an introductory stat class at UC Davis.? The class emphasizes the use of simulations, rather than mathematics, to get insight into statistics, and R is the mandated tool.?? A student in the class recently inquired about different approaches to sampling from a binomial distribution.? I've appended some code that exhibits the idea, the gist of which is that using

Mando este mensaje de respuesta para dar las gracias tanto a Pedro como a Carlos por sus sugerencias. Ahora ya tengo los números que quiero en la gráfica, me falta por quitar los que no quiero. Teniendo en cuenta lo que dice Pedro, voy a preguntar al autor de la librería. saludos, Fernando En martes, 9 de octubre de 2018 13:23:51 CEST, Carlos Ortega <cof en qualityexcellence.es>

Greetings: It would seem to me that the three arguments "a", "c" and "p" ought to produce the same result with a data frame that doesn't have any missing data which is not the case. What am I doing wrong or what don't I understand? > tmp <- data.frame(vol,con,mot,esp,pri,sec) > tmp vol con mot esp pri sec 1 1.00 120 90 78 21 1 2 0.50

Hello. Consider the following matrix: mp <- matrix(c(0,1/4,1/4,3/4,0,1/4,1/4,3/4,1/2),3,3,byrow=T) > mp [,1] [,2] [,3] [1,] 0.00 0.25 0.25 [2,] 0.75 0.00 0.25 [3,] 0.25 0.75 0.50 The eigenvectors of the previous matrix are 1, 0.25 and 0.25 and it is not a diagonalizable matrix. When you try to find the eigenvalues and eigenvectors with R, R responses: > eigen(mp) $values [1]

I have written a wrapper for heatmap.2 called heatmap.w.row.and.col.clust which auto-generates breaks using breaks<-round((c(seq(from=(-20 * stddev), to=(20 * stddev))))/20, digits = 2) #(stddev in this case = 2.5) This has always worked well in the past but now I am getting an error that non-finite breaks are being generated. Drilling down, it seems that my wrapper is generating finite

Dear all, I have some trouble understanding the chisq.test function. Take the following example: set.seed(1) A <- cut(runif(100),c(0.0, 0.35, 0.50, 0.65, 1.00), labels=FALSE) B <- cut(runif(100),c(0.0, 0.25, 0.40, 0.75, 1.00), labels=FALSE) C <- cut(runif(100),c(0.0, 0.25, 0.50, 0.80, 1.00), labels=FALSE) x <- table(A,B) y <- table(A,C) When I calculate the test statistic by hand

I'd like to annotate an xyplot with an R^2 value, but can not find the syntax to define the superscript format for the text. I'd appreciate suggestions, xyplot(SharkSloughEggs.df$Sharkeggs.rel + SharkSloughEggs.df$SharkHatched.rel + SharkSloughEggs.df$SharkFlooded.rel + HSI.shark$MEAN ~ Year, pch=c(1,9,5,4), lty=c(1,6,3,4), lwd = c(2), col = c("black",

Hi, I want to customise the segments on an xyplot. Below is a simple example of what I'm trying to do... #Example dataset x <- c(-0.25, 0.25, 0.8) y <- c(-0.5, 0, 0.75) gp <- c("A", "I", "C") my.data <- cbind.data.frame(x,y,gp) #setting up the parameters to customise the lines with. ltype <- c(1,2,3) env.col <-

Hello all, I have a very simple set of data and I would like to analyze them with probit analysis. The data are: X Event Trial 100 8 8 75 8 8 50 6 8 25 4 8 10 2 8 0 0 8 I want to estimate the value of X that will give a 95% hit rate (Event/Trial) and the corresponding 95% CI. Anyone can offer some help? Thanks!! -

On 2016-05-25 19:13, Kelly Lesperance wrote: > Hdparm didn?t get far: > > [root at r1k1 ~] # hdparm -tT /dev/sda > > /dev/sda: > Timing cached reads: Alarm clock > [root at r1k1 ~] # Hi Kelly, Try running 'iostat -xdmc 1'. Look for a single drive that has substantially greater await than ~10msec. If all the drives except one are taking 6-8msec, but one is very