search for: epsilons

Hello all, I'm in the process of moving over my Samba server (using LDAP). I believe everything is functioning correctly, except for this error I get when nmbd starts. Looking back at my old server, it was apparently doing this as well... so it may not even affect needed functionality. Still, I'd like to figure out why it's happening! If anyone has an idea, please let me

Dear List: I'm working to construct a very large sparse matrix and have found relief using the SparseM package. I have encountered an issue that is confusing to me and wonder if anyone may be able to suggest a smarter solution. The matrix I'm creating is a covariance matrix for a larger research problem that is subsequently used in a simulation. Below is the latex form of the matrix if

In e1071 package/svm default epsilon value is set to 0.1 and not 0.5 as documentation says. R

Hi, I am trying to do run the following model saved in "C:/bugs/sus.bug" model { for (i in 1:n){ y[i] ~ dpois(lamdba[i]) log(lambda[i]) <- mu+bmale[male[i]]+bschn[schn[i]]+epsilon[i] # epsilon[i] ~ dnorm(0,tau.epsilon) } mu ~ dnorm(0,.0001) bmale ~ dnorm(0,.0001) tau.epsilon <- pow(sigma.epsilon, -2) sigma.epsilon ~ dunif(0,100) for (j in

Hi I am doing this sort of thing: POLY: > > obj = best.tune(svm, similarity ~., data = training, kernel = "polynomial") > summary(obj) Call: best.tune(svm, similarity ~ ., data = training, kernel = "polynomial") Parameters: SVM-Type: eps-regression SVM-Kernel: polynomial cost: 1 degree: 3 gamma: 0.04545455 coef.0: 0

With respect to calculating the epsilon index of sphericity for ANOVA, discussed on pp. 45-47 of: http://www.psych.upenn.edu/~baron/rpsych.pdf It notes that epsilon is not required for a repeated measures design with only k=2 levels, as the minimum value of epsilon (e) is given by: e = 1/(k-1) so for k=2, we have e = 1 (ie, no correction of the F test df; see p. 46). These notes apply to a

Dear R users, I’d like to create a function as: Y.t+1 = Y.t + (1\p)*summation(x(Y.t,Y.t-1,...)) + epsilon.t where x is a function of Y.t, Y.t-1 and so on, epsilon is a random error and p is a parameter. Do you think something of the following form might be appropriate? Y<-function(Y,p,x,epsilon){ for (i in 2:length(Y)) {

...an additional fourth between subjects factor D. Everything works fine using aov(val ~ A*B*C + Error(subject/ (A*B*C) ) ) or aov(val ~ (D*A*B*C) + Error(subject/(A*B*C)) + D ) val, A, B, C, D and subject are columns in a data.frame. How can I get the estimated Greenhouse-Geisser and Huynh-Feldt epsilons? I know Peter Dalgaard described it in R-News Vol. 7/2, October 2007. However, unfortunately I am not able to apply that using my data... Furthermore, I am still confused of how SPSS calculates the epsilons since it is mentioned that perhaps there are any errors in SPSS?? I would be glad if any...

When `length( skewed.probs ) > 200' uniform samples are generated in R-devel. R-3.5.1 behaves as expected. `epsilon` can be a lot bigger than illustrated and still the uniform distribution is produced. Chuck > set.seed(123) > > epsilon <- 1e-10 > > ## uniform to 200 then small > p200 <- prop.table( rep( c(1, epsilon), c(200, 999-200))) > ## uniform to 201

I'm an experimental psychologist and when I run ANOVA analysis in SPSS, I normally ask for a test of non-sphericity (Box's M-test). I also ask for output of the corrections for non-sphericity, such as Greenhouse-Geisser and Huhn-Feldt. These tests and correction factors are commonly used in the journals for experimental and other psychology reports. I have been switching from SPSS to R

Dear all, I have a big problem to compile R-3.0.2 on our SUSE SLES 11 Server. Make breaks up with fortran errors and so the installation isn't successful This is a part from the make run output.: gcc-3.3 -fpic -L/usr/lib64/gcc-lib/x86_64-suse-linux/3.3.3-hammer/ -lg2c -ffloat-store -c dlamch.f -o dlamch.o dlamch.f: In function `dlamch': dlamch.f:89: warning: INTRINSIC

Hi!! I am trying to generate data with specific correlation using corgen method from the ecodist package. It does not seem to generate the data properly. I am listing the code below. Secondly, when I put the code given below all in one file and source it, it is unable to complete the task. But when I execute it one at a time it is able to complete it. Can someone point out any mistake that I may

I have a question about data mining. I have a dataset of 70 instances with 14 features that belong to 4 classes. As the number of each class is not enough to obtain a good accuracy using some classifiers( svm, rna, knn) I need to "oversampling" the number of instances of each class. I have heard that there is a method to do this. It consists in generating these new instances as follows:

It's not a ls bug. I've stepped through the code with gdb and it looks just fine. At this point I think Epsilon (a 32-bit app) is corrupting the image of its child process in a strange way. I'm working with the author at Lugaru (who's very responsive) to track it down. He couldn't reproduce it right away. I just reproduced it on a virgin CentOS 8 image at Linode with

This is not an R question but if anyone can help me, it's much appreciated. Suppose I have a series ( stationary ) y_t and a series x_t ( stationary )and x_t has variance sigma^2_x and epsilon is normal (0, sigma^2_epsilon ) and the two series have the relation y_t = Beta*x_t + epsilon My question is if there are particular values that sigma^2_x and sigma^2_epsilon have to take in

Hi! Let's go back to this topic please! I have to replace the Windows NT 4.0 server with Samba but I still don't know how to do this. I need to allow to someone (some user group) the right to add files into the folder. They use this "feature" on current NT server ver often and to this in the following ways: 1. Rightclick on file you want to add, Copy, then go to server, for

Hello, I am trying to simulate binary outcome data for a logistic regression Monte Carlo study. I need to eventually be able to manipulate the structure of the error term to give groups of observations a random effect. Right now I am just doing a very basic set up to make sure I can recover the parameters properly. I am running into trouble with the code below. It works if you take out the object

Dear R users, I am having some problems with glm. The first is an error message "subscript out of bounds". The second is the fact that reasonable starting values are not accepted by the function. To be more specific, here is an example: > success <- c(13,12,11,14,14,11,13,11,12) > failure <- c(0,0,0,0,0,0,0,2,2) > predictor <- c(0,80*5^(0:7)) >

Hi, A. In a nutshell: The training error, obtained as "error (ret)", from the return value of a ksvm () call for a eps-svr model is (likely) being computed wrongly. "nu-svr" and "eps-bsvr" suffer from this as well. I am attaching three files: (1) ksvm.R from the the kernlab package, un-edited, (2) ksvm_eps-svr.txt: (for easier reading) containing only eps-svr

In my last e-mails, I have asked for help regarding 1. 'defining functions inside loops' 2. 'integrating functions / vector arithmetics' 3. 'vectors out of lists?' 4. 'numerical integration' Since some of these topics seemed to be relevant (I'm guessing by the # of replies I got), I'm posting a modified section of my code. Any thoughts on improvements would