similar to: Fractional Factorial - Wrong values using lm-function

Hi, HardCloud (www.hardcloud.org) is an extension to the OpenMP 4.X standard that seeks to ease the task of offloading IP-cores to FPGA accelerators in CPU-FPGA architectures. This is achieved by two new clauses [use] and [module] shown in the example below: #pragma omp target device(HARP | HARPSIM | Catapult) map(to: X) map(from: Y) #pragma omp parallel for use(hrw) module(loopback) check

Hello, R users, I have two factors (treat, section) anova design experiment where there are 3 replicates. The objective of the experiment is to test if there is significant difference of yield between top (section 9 to 11) and bottom (section 9 to 11) of the fruit tree under treatment. I found that there are interaction between two factors. I wonder if I can contrast means from levels of

useR's, I am trying to find a quick way to change some values in a list that are subject to a condition to be NA. Consider the 3x1 matrix: delta <- matrix(c(2.5,2.5,1), nrow = 1) And consider the list named v that has 3 elements > v v[[1]] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [1,] 4.25 3.25 2.25 1.25 0.25 0.75 1.75 2.75 3.75 4.25

I''m trying to learn rails as I go along, and having a bit of trouble. There is an undefined method cropping that I don''t know why rails thinks should be there. Firstly, I''m using rails 3, ruby 1.9.2 I have a controller with an index action This part works fine, but i am trying to add a comment form to the page that is rendered by that index action. Supposing my

Hola a todos: Estoy intentado realizar un modelo senoidal de unos datos de radiación solar con el fin de afrontar el relleno de la serie y aplicar la prueba de Thom para verificar su homogeneidad [0]. De momento me encuentro con los siguientes problemas: 1- ¿Existe la prueba de Thom en R? ¿O debo crearme mi propia función? 2- Para la realización del modelo senoidal estoy siguiendo los pasos

I am trying to fit a very simple broken stick model using the package "segmented" but I have hit a roadblock. > str(data) 'data.frame': 18 obs. of 2 variables: $ Bin : num 0.25 0.75 1.25 1.75 2.25 2.75 3.25 3.75 4.25 4.75 ... $ LnFREQ: num 5.06 4.23 3.50 3.47 2.83 ... I fit the lm easily: > fit.lm<-lm(LnFREQ~Bin, data=id07) But I keep getting an error

Want to hold up a bank in Latin? "Catapultam habeo. Nisi pecuniam omnem mihi dabis, ad caput tuum saxum immane mittam." (I have a catapult. Give me all the money, or I will fling an enormous rock at your head.) "Lawyers are like chemical weapons. Everybody gets screwed if they're let out."

I'm wondering if it's possible to use isolinux on a bootable CDR to boot an ISO9660 disk image off of the CDR's filesystem. I'm trying to make a multi-boot CD which is capable of booting both floppy images and smaller ISO9660 images (such as the debian netinst or DSL - damnsmall linux), and I am wondering if isolinux is capable of doing this (or something similar to this -

I am relatively new to R, so apologize up front for my long question, particularly if there is too much or too little information. I have a large time series data set where each subject's behavior was originally coded on .25s intervals for 3min task. I am trying to determine if the findings are different depending on the coding interval (i.e. Compare .25s to 1s to 5s to 10s). I also need to

How can I make sure the residual signal, after subtracting the trend extracted through some technique, is actually trend-free ? I would greatly appreciate any suggestion about some Stationarity tests. I'd like to make sure I have got the difference between ACF and PACF right. In the following I am citing some definitions. I would appreciate your thoughts. ACF(k) estimates the correlation

Thank you for any help with this: Using xattr so that I can manage a domain joined Samba server share with AD permissions. The underlying OS file perms are 777 and I have set the share with -R a+w to make sure that permissions for owner and group are the same. Getfacl returns: # file: deleteme.txt # owner: root # group: group_access user::rwx group::rwx group:group_access:rwx mask::rwx

Dear R users, I am trying to fit the following ANCOVA model in R2.4.0 Y_ij=mu+alpha_i+beta*(X_ij-X..)+epsilon_ij Particularly I am interested in obtaining estimates for mu, and the effects alpha_i I have this data (from the book Applied Linear Statistical Models by Neter et al (1996), page 1020) y<-c(38,43,24,39,38,32,36,38,31,45,27,21,33,34,28)

Hello all, I'm trying to use confint from the MASS package to compute confidence intervals for an nls object. When I plot the results, however, they don't make sense - lines cross over the fitted model or just don't match the data. Code is : Thanks for help dat<-data.frame(a,b) with(dat, plot(a,b)) model<-(nls(b~(1/exp(a*x))*n, data=dat, start=list(x=.001,n=20),

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 R users, I'm here trying to understand correlated residuals in nonlinear estimation. I'm reading/studying the book Bates, D. M. and D. G. Watts, (1988), /Nonlinear regression analysis and its applications/, Wiley, NY. pages 92-94, trying to reproduce the figures and to find out the code in R to perform the necessary calculations. I also consulted Pinheiro and Bates, but without

dear R-users, I am facing a quite regular and basic problem when it comes to dealing with datasets, but I cannot find any satisfying answer so far. I have a messy dataset of galaxies like that : And XVIII 000214.5+450520 0.69 17 9 0.00 -8.7 26.8 6.44 6.78 < 6.65 -44 0.5 MESSIER031 0.6 1.54 PAndAS-03 000356.4+405319 0.10 17 0.00 -3.6 27.8 4.38

Hi R users, I have a dataframe in the below format xyz 01/03/2007 15.25 USD xyz 01/04/2007 15.32 USD xyz 01/02/2008 23.22 USD abc 01/03/2007 45.2 EUR abc 01/04/2007 45.00 EUR

Hello, R experts, If I understand Ted's anwser correctly, then I can not contrast the mean yields between sections 1-8 and 9-11 under "Trt" but I can contrast mean yields for sections 1-3 and 6-11 because there exists significant interaction between two factors (Trt:section4, Trt:section5). Could I use the commands below to test the difference between sections 1-3 and 6-11 ?

Hi All, I have the following text file (mytextfile.txt) 738307 527178 714456 557955 #N/A 17.42 6.22 4.73 #N/A 17.3 6.23 4.75 #N/A 17.29 6.17 4.7 #N/A 17.07 6.12 4.6 #N/A 17.27 6.19 4.7 #N/A 17.72 6.4 4.78 #N/A 17.12 6.19 4.75 #N/A 17.07 6.15 4.65 #N/A 17.03 6.07 4.64 #N/A 17.38 6.13 4.7 #N/A 17.38 6.13 4.7 #N/A 17.38 6.13 4.7 #N/A 17.38 6.13 4.7 #N/A

I am trying to `cut' a continuous variable into contiguous classes containing approximately an equal number of observations. I thought quantile() was the appropriate function to use in order to find the breakpoints, but I end up with classes of different sizes - see example below. Does anybody have an explanation for that? And what is the `recommended' way of computing what I am looking