Using weakly informative priors is almost always a better option. # Median :24.00 Mode :character Mode :character # 1st Qu.:18.00 Class :character Class :character # Median :6.000 Mode :character Mode :character Median :17.00 # 1st Qu.:4.000 Class :character Class :character 1st Qu.:14.00 # Mode :character Mode :character Median :3.300 Median :2004 # Class :character Class :character 1st Qu.:2.400 1st Qu.:1999 Summary(mpg) # manufacturer model displ year # Attaching package: 'brms' # The following object is masked from 'package:stats': # to the package is available through vignette('brms_overview'). # x dplyr::lag() masks stats::lag() library(brms) # Loading required package: Rcpp # Loading 'brms' package (version 2.16.3). # x dplyr::filter() masks stats::filter() Our goal is to estimate the relationship between engine size and highway MPG. To get started we’ll need to load the tidyverse and brms R packages and load in the data.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |