similar to: Cross-validation error with tune and with rpart

Dear all, In a greenhouse experiment we tested performance of 4 different species (B,H,P,R) under 3 different water levels in 10 replications. As response variable e.g. the number of emerging sprouts were measured on three dates. A simple Anova considering every measurement date separately shows a higly significant effect of species and moisture (and partly the interaction of both). The

I've now tested with: > R.version.string [1] "R Under development (unstable) (2024-02-16 r85931)" and all of the previously mentioned examples now work as expected on macOS. Thanks for the quick fix, Jenny On Thu, Feb 15, 2024 at 8:02?AM Tomas Kalibera <tomas.kalibera at gmail.com> wrote: > > On 2/14/24 23:43, Jennifer Bryan wrote: > > Hello, > > >

Hello, I've noticed a specific type of pipe() usage that works in released R, but not in r-devel. In 4.3.2 on macOS, I can write to a connection returned by pipe(), i.e. "hello, world" prints here: > R.version.string [1] "R version 4.3.2 (2023-10-31)" > con <- pipe("cat") > writeLines("hello, world", con) hello, world But in r-devel on

Hi all, I created environment "mytoolbox" by : mytoolbox <- new.env(parent=baseenv()) Is there anyway I put it in the search path ? If you need some background : In a project, I often write some small functions, and load them into my workspace directly, so when I list the objects with ls(), it looks pretty messy. So I am wondering if it is possible to creat an

Hi I am trying to make glm() work to analyze a toy logit system. I have a dataframe with x and y independent variables. I have L=1+x-y (ie coefficients 1,1,-1) then if I have a logit relation with L=log(p/(1-p)), p=1/(1+exp(L)). If I interpret "p" as the probability of success in a Bernouilli trial, and I can observe the result (0 for "no", 1 for

Dear All, I would like to to group the Ticker by Industry and create file names from the Industry Factor and export to a txt file. I have tried the folowing ind=finvizAllexETF$Industry ind is then "Aluminum" "Business Services" "Regional Airlines" ind2=gsub(" " ,"",ind) ind3 [1] "Aluminum"

Hello R-list, I am trying to calculate a ridge regression using first the *lm.ridge()* function from the MASS package and then applying the obtained Hoerl Kennard Baldwin (HKB) estimator as a penalty scalar to the *ols()* function provided by Frank Harrell in his Design package. It looks like this: > rrk1<-lm.ridge(lnbcpc ~ lntex + lnbeerp + lnwinep + lntemp + pop, subset(aa,

Dear R readers: I have written a short lme.R function, which adds normalized coefficients and White heteroskedasticity-adjusted statistics to the standard output. Otherwise, it behaves like lm. This is of course trivial for experts, but for me and other amateur users perhaps helpful. y= rnorm(15); x= rnorm(15); z= rnorm(15); m= lme( y ~ x + z); print(summary(m)); produces something

Hello, is it possible to obtain type III sums of squares for a nested model as in the following: lmod <- lm(resp ~ A * B + (C %in% A), mydata)) I have tried library(car) Anova(lmod, type="III") but this gives me an error (and I also understand from the documentation of Anova as well as from a previous request (http://finzi.psych.upenn.edu/R/Rhelp02a/archive/64477.html) that it is

Dear R users I am trying to obtain p-values for (quasi)poisson lmer models, including Markov-chain Monte Carlo sampling and the command summary. > > My problems is that p values derived from both these methods are totally different. My question is (1) there a bug in my code and > (2) How can I proceed, left with these uncertainties in the estimations of > the p-values? > > Below