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I'd love to see a companion code walk through with R.

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New post on the blog:

Comparing smooths in factor-smooth interactions II

This time I look at how to use ordered factors w by-variable smooth, to fit a reference smooth plus difference smooths for the other levels #rstats #mgcv #R #statistics

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Just discovered: R tutorials by the University of Edinburgh's Coding Club

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Yesterday, at the last meeting of the Hamburg R User Group in this year, I had the pleasure to give a talk about Bayesian modelling and choosing (informative) priors in the rstanarm-package. You can download the slides of my talk here. Thanks to the Stan…

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#VanwardStatistics offers #statisticalservices to businesses, doctoral students, the general public, and to researchers in various fields. Check out more at:

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Somebody using tablet or iPad to use application?

I'm having trouble interpreting lm outputs and choosing best lm for a given set of data


I am trying to create a variable based on the smallest value of the other three variables, then generate a second variable to indicate where the value is from. I used the following codes but it did not work due to the NA:


A <- c(NA, 1, 2, 3, NA)
B <- c(1, 2, 3, NA, NA)
C <- c(3, 3, 1, 1, NA)

dat <- data.frame(cbind(A, B, C)) %>%
mutate(M = pmin(A, B, C, na.rm = TRUE)) %>%
mutate(N = ifelse(M == A, "A",
ifelse(M == B, "B",
ifelse(M == C, "C", NA))))
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