similar to: Bayes Factor

Hello R Community, Subject: Bayes Factor A Bayesian ANOVA of the form: competitionBayesOut <- anovaBF(biomass ~ clipping, data = competition) Returns the following Error message: Error in (function (classes, fdef, mtable) : unable to find an inherited method for function ?compare? for signature ?"BFlinearModel", "missing", "tbl_df"? My guess the problem is in

Hi all, For the R package bujar, the warnings below were generated on CRAN's Windows systems. The package uses some Fortran subroutines. I would appreciate any advice to eliminate the warnings. By the way, similar warnings were generated to some unrelated R packages as well: https://www.r-project.org/nosvn/R.check/r-oldrel-windows-ix86+x86_64/imputeTS-00check.html. Thanks in advance. Zhu

Dear All, When I tried to run the following code (taken from the *spdplyr* package vignettes): library(spdplyr) library(maptools) data(wrld_simpl) worldcorner <- wrld_simpl %>% mutate(lon = coordinates(wrld_simpl)[,1], lat = coordinates(wrld_simpl)[,2]) %>% filter(lat < -20, lon > 60) %>% dplyr::select(NAME) I got the following error messages: Error in (function (cl,

Dear all, I tried to rerun the examples given by Hyndman in otexts but keep on getting errors and I have searched through google but no solution yet. Thank you in advance for any help given. library(fpp3) library(lubridate) library(xts) library(fabletools) library(ggplot2) library(dplyr) library(gridExtra) > dput(head(new_us_retail_employment,100))structure(list(Month = structure(c(-11323,

Hi, I have a grouped data set and would like to calculate weighted proportions for a large number of factor variables within each group member. Rather than using dplyr::count() on each of these factors individually, the idea would be to do it for all factors at once. Does anyone know how this would work? Here is a reproducible example: ############################################################

I am currently having a problem where my bayes DB appears to be version 0 over and over again. spamassassin --lint -D 2>&1 | grep bayes bayes: bayes db version 0 is not able to be used, aborting! at /usr/lib/perl5/vendor_perl/5.8.0/Mail/SpamAssassin/BayesStore/DBM.pm line 160. I have SpamAssassin 3.0.3 installed: /etc/mail/spamassassin/local.cf contains: use_bayes 1 bayes_auto_learn 1

Hi, I need to classify, using Naive Bayes and Bayes Networks, and estimate their performance using cross validation. How can I do this? I tried the bnlearn package for Bayes Networks, althought I need to get more indexes, not only the error rate (precision, sensitivity, ...). I also tried the *e1071* package, but I could not find a way to do cross-validation. Thanks for everyone. Guilherme.

I am having trouble using back ticks with the R extractor function 'predict' and an lm() model.? I'm trying too construct some nice vectors that can be used for plotting the two types of regression intervals.? I think it works with normal column heading names but it fails when I have "special" back-tick names.? Can anyone help with how I would reference these?? Short of

Hi Paul, No need to collapse the information into a single text string, gregexpr() can take a vector of strings (sentences in your case). You can split your sentences up, number them how you want, then search for your pattern either via regex or via these extra packages you use which probably use the PCRE regex library anyway. However, as this is basically what you did, I'm not sure why

I am wondering if anybody here have a simple example in R for Naive Bayes. For example, I can do k-means clustering on the "iris" data - data(iris) cl <- kmeans(iris[,1:4], 3) cl$cluster cbind(1:150,iris$Species) =========== But how to do Naive Bayes classification in the same "iris" data? Many thanks! -- View this message in context:

Hi! I have dovecot, Spamassassin and postfix running. I started to use sa-learn to get better and more precise spam identification and filtering. I have not set the Bayes_path preference on my local.cf file, thus when I call sa-learn -u myuser at mydomain.org --spam, the Bayes DB gets updated at /root/.spamassassin. I decided then to create a sieve filter on dovecot, as described on

Hi Robert, Thank you for your reply. An attempt to solve this via a regular expression query is particularly helpful. Unfortunately, I don't have much time to play around with this just now. Ultimately though, I think I would like to implement a solution something along the lines of what you have done. I have a book on regular expressions that I am now starting to read. In the meantime, the

Hi, Currently I testing the packets that contain built-in features for classification. Actually I looked packages such as: e1071, Klar, Caret, CORElearn. However, from what I noticed when building a naive Bayesian classifier, that they package use of the finite mixture model to estimate P (x | C) and using a normal distribution. In my research I use binary data and I want modeled P (x | C), eg the

hi there!! i am trying to implement the code of the e1071 package for naive bayes, but it doens't really work, any ideas?? i am very glad about any help!! i need a naive bayes with 10-fold cross validation: code: library(e1071) model <- naiveBayes(code ~ ., mydata) tune.control <- tune.control(random = FALSE, nrepeat = 1, repeat.aggregate = min, sampling = c("cross"),

?s 17:38 de 30/11/2023, Robert Baer escreveu: > I am having trouble using back ticks with the R extractor function > 'predict' and an lm() model.? I'm trying too construct some nice vectors > that can be used for plotting the two types of regression intervals.? I > think it works with normal column heading names but it fails when I have > "special"

Dear R users, I'm glad to announce the release of a new package on CRAN for exploring correlations in R: corrr <https://cran.rstudio.com/web/packages/corrr/index.html> . corrr provides a handful of methods to create and explore a correlation tbl (rather than a matrix). E.g., rearrange() the correlations based on their strength, or focus() on selected variables against others. All

Dear R users, I'm glad to announce the release of a new package on CRAN for exploring correlations in R: corrr <https://cran.rstudio.com/web/packages/corrr/index.html> . corrr provides a handful of methods to create and explore a correlation tbl (rather than a matrix). E.g., rearrange() the correlations based on their strength, or focus() on selected variables against others. All

Hello fellow R programmers, I'm trying to use package e1071's naiveBayes function to create a model with weighted data. See example below, variable "d" is a count variable that provides the # of records for the given observation combination. Is anyone aware of a "weight" argument to this method? I've been unsuccessful in my research. Thanks, Mike

Dear all, I am trying to get the emperical bayes estimates together with their standard errors out of lme4. Up to now I have used MLwiN to get these estimates. I have fitted the following - very simple - model, just to find out how this works. test<-lmer(y~(1|subject),data,REML=F) ranef(test,postVar=T) str(ranef(test,postVar=T) If I use the formulation of the emperical bayes estimates and

Hello All, I need some help figuring out how to extract combinations of target words/terms from cancer patient text medical records. I've provided some sample data and code below to illustrate what I'm trying to do. At the moment, I'm trying to extract sentences that contain the word "breast" plus either "metastatic" or "stage IV". It's been some