multiple regression? [General Sta­tis­tics]

posted by Helmut Homepage – Vienna, Austria, 2017-10-08 19:17 (2825 d 07:31 ago) – Posting: # 17875
Views: 18,125

Hi ElMaestro,

nice setup. Given

❝ […] a lot of knobs and buttons and sliders that allow me to tweak combinations of:

❝ - Tesla coil zap modifier strength

❝ - Evil discharge combobulator intensity

❝ - Ion stream barbaric voltage gain

❝ - Apocalyptic wolfram anode ray modulation

❝ ...and so forth.


I’m I right that you are aiming at multiple regression (i.e., >1 regressor and and one regressand)? See there for an arsenal of methods. For the same number of regressors the adjusted R2 takes the number of data points into account.

x1 <- rnorm(10)
y1 <- x1*2+rnorm(10, 0, 0.1)
muddle1 <- lm(y1 ~ x1)
R2.adj1 <- summary(muddle1)$adj.r.squared
x2 <- x1[-1] # drop 1
y2 <- y1[-1] # drop 1
muddle2 <- lm(y2 ~ x2)
R2.adj2 <- summary(muddle2)$adj.r.squared
cat(R2.adj1, R2.adj2, "\n")


Dif-tor heh smusma 🖖🏼 Довге життя Україна! [image]
Helmut Schütz
[image]

The quality of responses received is directly proportional to the quality of the question asked. 🚮
Science Quotes

Complete thread:

UA Flag
Activity
 Admin contact
23,426 posts in 4,929 threads, 1,682 registered users;
41 visitors (0 registered, 41 guests [including 29 identified bots]).
Forum time: 02:48 CEST (Europe/Vienna)

Half the harm that is done in this world
Is due to people who want to feel important.    T. S. Eliot

The Bioequivalence and Bioavailability Forum is hosted by
BEBAC Ing. Helmut Schütz
HTML5