similar to: How to set parameters constraints in a function?

I have tried to print a table of greek alphabet names and symbols without success. I can print one character at a time but can't seem to find a way to automate an entire list of the symbols. Some of the code I have tried is below. I have searched on help, worked the examples in the December 2002 R Help Desk article and plotmath but have not been able to find a way to accomplish the

Dear R users, When I was trying to use the function *optim* to get the MLEs, quite a few warning messages showed up as below: Warning in log(psi * lam) : NaNs produced I am just wondering what does this mean? Was it something wrong with my likelihood function or was it sth wrong with the data? Thanks in advance. Carol Gao [[alternative HTML version deleted]]

Dear R-user, Did anybody know how to calculate the kappa statistics of two vectors for the agreement? for example: a<-c(0,1,0,0,1,0) b<-c(0,1,1,0,0,1) I know the percent of agreement is 3/6, but how to get the kappa? [[alternative HTML version deleted]]

Hello, I?m looking for a way to measure the goodness of fit of my model with Cohen?s Kappa (scaling between 0 and 1). The kappa function does not give the results I?m looking for. Heres the code: z<-glm(x~y,binomial) kappa(z, exact = T) Does anyone know more? many thanks Christian -- _______________________________________________ Search for businesses by name, location, or phone number.

Hello, I'm new to R but wan't to use it to compute the statistics of my medical study. The study includes several parameters for a number of patients. Each parameter was assessed by a number of readers, once with a special condition, once without. Now I have a data.frame with colums like: PatientID, ReaderID, SpecialCond(yes/no), Parameter1, Parameter2..... the rows are not sorted, and

Hi, R guys: I'm using L-BFGS-B method of optim for minimization problem. My function called besselI function which need non-negative parameter and the besselI will overflow if the parameter is too large. So I set the constraint box which is reasonable for my problem. But the point outside the box was test, and I got error. My program and the error follows. This program depends on CircStats

Hi All: Could anyone point me to a package that can calculate stratified kappa? My design is like this, 4 raters, 30 types of diagnosis scores, 20 patients. Each rater will rate each patient for each type of diagnosis score. The rater's value is nominal. I know I can measure the agreement between raters for each type of diagnosis score, e.g., calculate out 30 kappa values. My problem is I

Is there a function that calculates the inter-rater agreement index (kappa) in R? Thanks ../Murli [[alternative HTML version deleted]]

Are there functions available computing the gamma-correlation for ordinal scaled variables and kappa-accuracy for nominal variables, thanks, Mark ........................................................................... Swiss Federal Institute for Forest, Snow and Landscape Research Zuercherstrasse 111 - 8903 Birmensdorf - Switzerland e-mail: markus.schwarz at wsl.ch www:

Hi, I am having problems getting cohen's kappa to work. I have been using the function: ><-ckappa(x,y) from the psy package. I am trying to test for inter-observer reliability, I have 2 observers and 26 categories, however, the two observers might not necessarily have the same range of categories (I have unequal score ranges). However, I thought R could cope with this. Each time I

Hello, Consider MCMC sampling with metropolis / metropolis hastings proposals and a density function with a given valid parameter space. How are MCMC proposals performed if the parameter could be located at the very extreme of the parameter space, or even 'beyond that' ? Example to express it and my very nontechnical 'beyond that': The von Mises distribution is a circular

Hello, When evaluating different learning methods for a categorization problem with the (really useful!) caret package, I'm getting confusing results from the Kappa computation. The data is about 20,000 rows and a few dozen columns, and the categories are quite asymmetrical, 4.1% in one category and 95.9% in the other. When I train a ctree model as: model <- train(dat.dts,

Hi, im little bit confused about Cohen's Kappa and i should be look into the Kappa function code. Is the easy formula really wrong? kappa=agreement-chance/(1-chance) many thanks christian ############################################################################### true-negativ:7445 false-positive:3410 false-negativ:347 true-positiv:772 classification-aggrement:68,6%

Greetings, I am a bit confused by the results returned by the functions: cohen.kappa {concord} classAgreement {e1071} when using a two-way table. for example, if I have an matrix A, and a similar matrix B (same dimensions), then: matrix A and B can be found: http://casoilresource.lawr.ucdavis.edu/drupal/files/a_40.txt http://casoilresource.lawr.ucdavis.edu/drupal/files/b_40.txt A <-

Hi all, I have a list of 20000 data, and the list look like below. I wonder what is the simplest way to extract 'kappa' value (or 'xi' or 'alpha' for the matter) from each of the data. How can I simply code it without having to change the list to a dataframe first? Many thanks! $X19997 xi alpha kappa 784.7718640 165.4065141 -0.2709599 $X19998

Dear list, I'm migrating a project from Matlab to R, and I'm facing a relatively complicated problem for nls. My objective function is below: >> objFun <- function(yEx,xEx,tEx,gamma,theta,kappa){ yTh <- pdfDY(xEx,tEx,gamma,theta,kappa) sum(log(yEx/yTh)^2) } The equation is yTh=P(xEx,tEx) + noise. I collect my data in: >> data <-

Dear R-users I need to calibrate kappa, rho, eta, theta, v0 in the following code, see below. However when I run it, I get: y <- function(kappahat, rhohat, etahat, thetahat, v0hat) {sum(difference(k, t, S0, X, r, implvol, q, kappahat, rhohat, etahat, thetahat, v0hat)^2)} > nlminb(start=list(kappa, rho, eta, theta, v0), objective = y, lower =lb, > upper =ub) Error in dots[[1L]][[1L]] :

Dear all, I have a question on Cohen's kappa: Assume I have two datasets, one has 500 objects, 10 methods and the other, 1000 different objects, 20 different methods. Could I compare between the two datasets to conclude the 10 methods are more "concordant" than the 20 ones by looking at some output, for example, cohen.kappa{concord} ? One more, could anyone explain in brief,

I am a novice user of "R" and I'm learning with R version 2.8.1, using WinEdt_1.8.1, under Widows Vista Home Version. ## The test function below, from a vector input, returns vector values: # and it contains an "ifelse"statement TEST<- function(x) { low<- -x^2 up<- x^4 ifelse(x>=0,up,low ) } u<- seq(-1,1,0.5) TEST(u)

Hi, I've noticed I get different results fitting a function to some data on my laptop to when I do it on my computer at work. Here's a code snippet of what I do: ##------------------------------------------------------------------ require(circular) ## for Bessel function I.0 ## Data: dd <- c(0.9975948929787, 0.9093316197395, 0.7838819026947, 0.9096108675003, 0.8901804089546,