similar to: x tick labels - sparse?

Hi, I would like to produce a plot with a symbol on every nth point in a time series data, like the one in the following: http://www.phon.ucl.ac.uk/home/yi/ProsodyPro/EnglishFocus.png x <- seq(-100,1000,25) plot(x,type="l") Could someone help me out with the above example? Thanks.... [[alternative HTML version deleted]]

Hi, this is my first help request so please bear with me. I've been running some normality tests using the nortest package. For some of my datasets the Cramer-von Mises normality test generates an extremely high probability (e.g., 1.637e+31) and indicates normality when the other tests do not. Is there something I'm misunderstanding or potentially a bug in the code? Below are the

I believe there to be a bug in the cvm.test module of the nortest package authored by Juergen Gross. I do not know how to contact the author directly. I've been running some normality tests using the nortest package. For some of my datasets the Cramer-von Mises normality test generates an extremely high probability (e.g., 1.637e+31) and indicates normality when the other tests do

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 =

Dears, I'm trying to find the parameters (a,b, ... l) that optimize the function (Model) described below. 1) How can I set some constraints with MLE2 function? I want to set p1>0, p2>0, p3>0, p1>p3. 2) The code is giving the following warning. Warning: optimization did not converge (code 1) How can I solve this problem? Can someone help me? M <- 14 Y = c(0, 1, 0, 0, 0,

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

Please help me to produce smoothed contour plots. I have dependent data generated at regular intervals of two independent variables and would like to produce smoothed contour plots - I cannot get interp (alima) to produce cubic interpolations of the data, only linear ones. I'm interested in smoothing as the data generation process is stochastic and produces small variations which I'd

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

I have panel data in the following form: TIME X1 S1 1 1 0.99 1 2 0.50 1 3 0.01 2 3 0.99 2 1 0.99 2 2 0.25 3 3 0.75 3 2 0.50 3 1 0.25 ... ... ...... And desire a new vector of observations in which one column (S1 above) is sorted for each second from least to largest. That

This may not actually be an R/Splus problem, but it started off that way ..... ===+===+===+===+===+===+===+===+===+===+===+===+===+===+===+===+===+===+=== Executive summary: ================== Simulations involving extreme value distributions seem to ``work'' when the underlying distribution is exponential(1) or exponential(2) == chi-squared_2, but NOT when the underlying distribution is

I've loaded R-0.50-a1 but when I try to apply the patches it cannot find the files to apply patches to. [9] gilp/R0.50 : patch <R-0.50-a1.patch1 Looks like a new-style context diff. File to patch: [10] gilp/R0.50 : [10] gilp/R0.50 : [10] gilp/R0.50 : cd R-0.50-a1 [11] gilp/R0.50/R-0.50-a1 : ls CHANGES RESOURCES configure.mac* COPYING TASKS configure.win* COPYRIGHTS TASKS.OLD

Hi R-users, I am using "postscript("xx.eps", horizontal=FALSE, onefile=FALSE, height=6, width=10, pointsize=10)" and "barplot(xx.dat)" in R to produce EPS graphics for LATeX document. When checking the graphics with "gv" I see that it was not produced with full details. The main graphic is there, but axes labels and titles are missing. While checking the

Given a vector of numeric of length n, I need to find segments that are >= 0.2, compute the average of individual segments, and replace the original values in each segment by their corresponding averages. For example, there are three segments that are >= 0.2, the average of 1st segment is 0.3, 2nd is 0.5, and the 3rd is 0.5333333 >

I have noticed a significant performance degradation using merge in 2.9.1 relative to 2.8.1. Here is what I observed: N <- 100000 X <- data.frame(group=rep(12:1, each=N), mon=rep(rev(month.abb), each=N)) X$mon <- as.character(X$mon) Y <- data.frame(mon=month.abb, letter=letters[1:12]) Y$mon <- as.character(Y$mon) Z <- cbind(Y, group=1:12) system.time(Out

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

Dear all; I'm trying to create a 2 x 3 plot (something I know like lattice can do better) using the plot function. However; I'm not sure how to make the width of the plots to be the same on each column. I guess the answer maybe obvious but I haven't been able to figure it out. I'll appreciate any suggestion. Here is the (highly inefficient) code for the first row: par(mfrow =

Hello, I am trying to create multiple matrices (to run a PVA) but can't import all of them from a .csv without the numbers treated as labels and not factors. I can enter the matrix slowly: Site05_96 <- matrix(c(0.07,0,0.03,0.00,NA,0.00, 0.09,0.166666667,0.31,0.42,NA,0.00, 0.00,0,0.00,0.00,NA,0.00, 0.00,0,0.00,0.00,NA,0.00,

Hello everyone,           I have a basic question regarding logical operators. > x<-seq(-1,1,by=0.02) > x   [1] -1.00 -0.98 -0.96 -0.94 -0.92 -0.90 -0.88 -0.86 -0.84 -0.82 -0.80 -0.78  [13] -0.76 -0.74 -0.72 -0.70 -0.68 -0.66 -0.64 -0.62 -0.60 -0.58 -0.56 -0.54  [25] -0.52 -0.50 -0.48 -0.46 -0.44 -0.42 -0.40 -0.38 -0.36 -0.34 -0.32 -0.30  [37] -0.28 -0.26 -0.24 -0.22 -0.20 -0.18 -0.16

Hi, I'm having especially hard time today and couldn't find any clue/answer through the internet. ?I hope you can help. I'm in a process of writing a script to estimate error correction model, and I was following an example in Bernhard Pfaff's Analysis of Integrated and Cointegrated Time Series with R. ?I have the following price data: > head(series,15) ?? ? ? ? ? PX_SETTLE

Hi Step 1: I create a data.frame called iolm. Step 2: I create a conditional subset i_wtr. Step 3: In this subset I add 0.3 to all values in the IOLM_AST column. Step 4: Now I am looking for the best way to Œmerge¹ the altered subset back into the original iolm data.frame ## STEP 1 >iolm ID IOLM_AST IOLM_AXIS 1 1 1.15 165.33 2 2 1.20 79.00 3 3 0.40