aufrank

library(rms)
library(ggplot2)
ddiamonds <- datadist(diamonds)
options(datadist = "ddiamonds")
fit.ols <- ols(price ~ carat * cut, diamonds)

## can specify a range on a continuous predictor 
Predict(fit.ols, carat = seq(2,4,.25))

## can specify a single level for a categorical predictor

aufrank

[diff]
	tool = chdiff

[difftool]
	prompt = false

[difftool "chdiff"]
	cmd = /usr/bin/env chdiff "$LOCAL" "$REMOTE"

aufrank

Day job:  Cognitive science post-doc

Favorite Python project:  PsychoPy https://github.com/psychopy/psychopy

Favorite Conference:  International Workshop on Language Production

Python Experience Level:  Intermediate

aufrank

(defrecord Node [^Float activation neighbors])

(def k (Node. 0.2 '(kaet)))
(def ae (Node. 0.2 '(kaet)))
(def t (Node. 0.2 '(kaet)))
(def kaet
  (Node. 0.2 '(k ae t cat)))
(def cat (Node. 0.2 '(kaet)))

(map #(:activation %) (:neighbors kaet))