similar to: longer object length, is not a multiple of shorter object length in: kappa * gcounts

Hi, I want to fit a kernel density estimator by bkde of library KernSmooth. I need only the density value at the point 0. I do not understand the following behaviour: > q <- rnorm(100) > bkq <- bkde(q, bandwidth=0.11, gridsize=1, range.x=c(0,0)) Error in 0:L : NA/NaN argument > bkq <- bkde(q, bandwidth=0.11, gridsize=1, range.x=c(-1,1)) > bkq $x [1] -1 $y [1] NA > bkq

Hi, I have two separate questions relating to the KernSmooth package. I am using the dpik function from the KernSmooth package and receive the error Warning message: In kappam * Gcounts : longer object length is not a multiple of shorter object length I saw an earlier post , but the issue was using the bkde fxn and the person appeared to be using too small of a bandwidth.

On 27 April 2017 at 12:01, Johannes Ranke wrote: | | > so it seems to me this must affect all packages in Debian sid that were | > built before the release of R 3.4.0! | | or rather before 14 April 2017, which is when R from revision r72510 was | uploaded to sid as pre-release candidate. Another example with KernSmooth: > library(KernSmooth) KernSmooth 2.23 loaded Copyright

Am Dienstag, 25. April 2017, 11:21:31 schrieb Dirk Eddelbuettel: > On 25 April 2017 at 16:11, Johannes Ranke wrote: > | This looks similar to what I got this morning when I tested my > | (unreleased) > | backport of R 3.4.0 to Debian jessie. My test was > | > | library(MASS) > | example(rlm) > | > | and there was an object that was not found. I am on a train on the way

Any advice when to use denstity() and when the KernSmooth package bkde() to smooth a histogram? No specific problem to use either one, but I'm curious why there are two so similar implementations. Thanks! mario -- Ing. Mario Valle Data Analysis and Visualization Group | http://www.cscs.ch/~mvalle Swiss National Supercomputing Centre (CSCS) | Tel: +41 (91) 610.82.60 v.

Hi, I have a vector or random variables and I'm estimating the density using "bkde" function in the KernSmooth package. The out put contains two vectors (x and y), and the R documentation calls y as the density estimates, but my y-values are not exact density etstimates (since these are numbers larger than 1)! what is y here? Is it possible to get the true estimated density at each

Thank you for your reply. I know the x in dpik() means the vector. But I don't know how to import into c() with a huge metadata (>1000). Following is my some try, and the h is: [1] 0.001180569, which seems to be feasible.

Hello, I wanted to know if there is a simple way of getting the inverse cdf for a KDE estimate of a density (using the ks or KernSmooth packages) in R ? The method I'm using now is to perform a numerical integration of the pdf to get the cdf and then doing a search for the desired probablity value, which is highly inefficient and very slow. Thanks, -fj [[alternative HTML version deleted]]

Dear Sir/Madam; Would you please tell me what is the command that allows the estimation of the Kernel Density for some data. Thanks, Thami Rachidi [[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.

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%

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, 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 All, I am using fleiss kappa for inter rater agreement. Are there any know issues with Fleiss kappa calculation in R? Even when I supply mock data with total agreement among the raters I do not get a kappa value of 1. instead I am getting negative values. I am using the irr package version 0.70 Any help is much appreciated. Thanks and Regards M [[alternative HTML version deleted]]

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,

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

Hallo all, I am looking for an R implementation of the four parameter kappa distribution (cdf, pdf, quantile, and ransom numbers), or at a minimum, the generalized logistic distribution. Any suggestions? Thank you very much, Serguei

Dear list, I calculated the kappa-accuracy for two differnt classifications. How can I test now the two kappa-value for significance? thanks, Mark ..................................................................... Markus Schwarz Wissenschaftliche Mitarbeiterin Eidg. Forschungsanstalt WSL Forschungsprogramm Musterland Z??rcherstrasse 111 CH-8903 Birmensdorf Telefon +41-44-739 22 87 Fax

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: 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