similar to: Dividing tick-data into intervalls

Hi everyone, I've got a question concerning the function Box.test for testing autocorrelation in my data. My data consist of (daily) returns of several stocks over time (first row=time, all other rows=stock returns). I intend to perform a Box-Ljung test for my returns (for each stock). Since I have about 3000 stocks in my list, I'm not able to perform the test individually for each

Hi I have a plist t which contains size measurements of individual plants, identified by the field "plate". It contains, among other, a field "year" indicating the year in which the individual was measured and the "height". The number of measurements range from 1 to 4 measurements in different years. My problem is that I would need the LAST measurement. I only

Dear list, I am trying to create a three-way table with percent occurrence instead of raw frequencies. However, I cannot get the results I expected: I have the following table: > ftable(table( mannerDF$agem, mannerDF$target, mannerDF$manner )) <snip> 50 bak 0 0 0 0 1 0 pak 0 0 0 0 3 0 sak

Hi, I have a function that approximates some data and indicates "segments". I'd like to plot the original data, and then the linear approximations on top of it. (Ideally, just a subset of N rows at a time, as the data set is large.) I can't figure out a clean way to do this. Suggestions? here is some sample data: ================================== Row X Seg ?.

Dear R experts, I have a Matlab code which I am translating to R in order to examine and enhance it. First of all, I need to reproduce in R the results which were already obtained in Matlab (to make sure that everything is correct). There are some matrix manipulations and '\' operation among them in the code. I have the following data frame > ABS.df Pro syn

Hi r-sers, I have a data of relative frequencies for the interval of 0-20, 20-40,...380-400.  I would like the two data on the same graph using the same x-axis label.  My question is how to get a smooth curve using kernel density code if it possible for this data.   > cbind(rel_obs,rel_gen)           rel_obs rel_gen  [1,] 0.000000000  0.0000  [2,] 0.092534175  0.0712  [3,] 0.105152471  0.1092

I have a data set that I display using barplot. I don't know what you call it, but when I look at it, it looks like this: > lsu (0,0.1] (0.1,0.2] (0.2,0.3] (0.3,0.4] (0.4,0.5] (0.5,0.6] A 0.052631579 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 B 0.000000000 0.000000000 0.001007049 0.003021148 0.000000000 0.000000000 E 0.200000000 0.000000000

I have the following matrix: > dat [,1] [,2] [,3] [,4] foo 0.7574657 0.2104075 0.02922241 0.002705617 foo 0.0000000 0.0000000 0.00000000 0.000000000 foo 0.0000000 0.0000000 0.00000000 0.000000000 foo 0.0000000 0.0000000 0.00000000 0.000000000 foo 0.0000000 0.0000000 0.00000000 0.000000000 foo 0.0000000 0.0000000 0.00000000 0.000000000 and given this:

Hy Guys, My samba version: 4.0.13 ntp version: 4.2.6p3 Ubuntu 12.04.3 LTS I have a weird problem, I sat up the time service via https://wiki.samba.org/index.php/Configure_NTP On the servers I have no firewall. This port is open when i check with nmap, ntp runs. Looks like all of my Windows 7 clients works fine but w32tm /resync says Permission denied 0x8007005, so not that good :) Windows

Dear members. I am having problems to understand the kmeans- results in R. I am applying kmeans-algorithms to my big data file, and it is producing the results of the clusters. Q1) Does anybody knows how to find out in which cluster (I have fixed numberofclusters = 5 ) which data have been used? COMMAND (kmeans.results <- kmeans(mydata,centers =5, iter.max= 1000, nstart =10000)) Q2) When I

I have managed to create a data frame like this: > tsus_same_mean[1:10,] PID Grp Dist PercAln PercId 1 12638 Acidobacteria 0.000000000 1.0000000 1.0000000 2 87 Actinobacteria 0.000000000 0.9700000 0.9700000 3 92 Actinobacteria 0.008902000 1.0000000 0.9910000 4 94 Actinobacteria 0.000000000 1.0000000 1.0000000 5 189 Actinobacteria 0.005876733

Hi, I have the binned data (observed and generated from model)  that I would like to test using the anderson-darling goodness of fit test.  But I'm not sure which package in R to use. I tried ad.test(...) but it does not recognise the test by Vito Ricci in FITTING DISTRIBUTIONS WITH R   > ad.test(hist_hume_beec[,1],hist_hume_beec[,2]) Error: could not find function "ad.test"

Hi, I need further help with my GAMs. Most models I test are very obviously non-linear. Yet, to be on the safe side, I report the significance of the smooth (default output of mgcv's summary.gam) and confirm it deviates significantly from linearity. I do the latter by fitting a second model where the same predictor is entered without the s(), and then use anova.gam to compare the

I did this: nb <- naiveBayes(users, platform) pl <- predict(nb,users) nrow(users) ==> 314781 ncol(users) ==> 109 1. naiveBayes() was quite fast (~20 seconds), while predict() was slow (tens of minutes). why? 2. the predict results were completely off the mark (quite the opposite of the expected overfitting). suffice it to show the tables: pl: android blackberry ipad

Dear Wiza[R]ds, I have the following data in a data.frame. I need to do an anova with multiple comparison but I don't know how to factor the groups for analysis. There are 3 groups, 1,2 and 3 labelled in column 1. Help appreciated with thanks in advance. Group SI Sif SG Io I2 lol2 1 9.08e-05 9.08e+00 0.060842287 1.798556446 32.574500

Greetings all, Ran into a strange problem with the krige function from geoR. The problem that I am having is that while the krige function seems to work well, the resulting predicted values are all NAs. Given the size of the datasets I am working with can't attach it, but I can provide snippets of the datasets. > casedata station year month day obs mpe bias type

I have data matrix and I want to replace values. > try Rh.Rj RR.Rj RT.Rj V1 0.08465125 0.19159688 0.617294468 V2 0.74853203 0.88826790 0.113979660 V3 0.68767961 0.17979307 0.013802852 V4 0.31722379 0.25611821 -0.021954454 V5 0.17931687 0.04491838 0.011484522 V6 0.87455663 0.16846121 0.002241211 V7 0.61770029 0.01090132 0.000079900 > try[try > 0.05]<-0 >

I have 2 vectors, x and y and have done an xy plot. I want to plot the label (name?) of the vector on the plot rather than the value. text(x,y, labels = x) gives me the value of x. text(x,y, labels = labels(x)) gives me something like c("text1","text2"..) plotted for each point text(x,y, labels = names(x)) gives nothing print(x) gives me [,1] text1

Hi, This is a beginner R question. I have a 4x4 matrix named 'lookup' with the following values: 1 2 3 4 1 0.000000 2.828427 5.656854 8.485281 2 2.828427 0.000000 2.828427 5.656854 3 5.656854 2.828427 0.000000 2.828427 4 8.485281 5.656854 2.828427 0.000000 I then create a new empty matrix named 'dd' with specfic row and col names :

Hello, I am Souradeep Chattopadhyay and I am a graduate student at Iowa State University Department of Statistics. Can anyone please explain the mathematical formulation behind the scaling matrix returned by the qda function in MASS package. I want to understand how this scaling matrix is derived from the inputs given to the qda function. Example Code The following example is using