Operating System: Microsoft Windows [Version 10.0.17134.345]
brms Version: 2.5.0
I want to fit a binomial brms model containing the weight option. I have followed the instructions discussed here but when I try using the code and data below I get the error:
Just another, related question, if you don’t mind:
I would like to get proportions r/n of the expected values of the response and the posterior samples of the response, instead of N*p from the output of fitted() and predict() functions as discussed here.
I am doing multinomial logit regression of survey data.
My dependent variable has three levels 1,2,3. I divied the data set 1 as reference value that named as training and 2,3 as testing value. When I go for prediction of training it Works. But when I go for testing values,
pred2<- predict(m1,data=testing)
tab2<- table(pred,(testing$CCS))
(CCS is DV of my model)
Then, it comes like this
Error in testing$CCS : $ operator is invalid for atomic vectors
Its coming the same error!
I checked
is.vector(testing)
hy everyone.
I’m new on Rstudio and i’m using it for some econometrics stuff.
I have a error message : “Error in result$V2 : $ operator is invalid for atomic vectors”
I’m trying to do a linear regression on a data that I have simulate myself using Var-covariance matrix.
When a try to run the regression I have the error message above in " ".
there is my code:
read.csv(“C:/Users/Romain Lugand/Desktop/Romain/travail/MASTER/Economie_Psychology/Metrics/M1EP_Q1_2020-21.csv”)
rom <- set.seed(24)
summary(“rom”)
Two issues here. When specifying regressions in lm, you only need to specify the variable name (without the result$ prefix) and then specify which dataset the variables belong to. Additionally, the rmvnorm function returns a matrix, whereas lm only accepts a data.frame.