set terminal svg fname "Helvetica" fsize 25 set output "LinearRegression.svg" set key left set xtics axis 1,1 set ytics nomirror 1 set border 2 f(x) = a*x + b fit f(x) 'randpts' using 1:2 via a,b set yrange [-0.9:4] plot 'randpts' with points pointtype 7 pointsize 0.3 title 'Datapoints', f(x) with lines linetype 3 linewidth 3 title 'Regression', 0 with lines linetype -1 notitle
The datafile 'randpts' was made in Octave using the commands
f = fopen('randpts', 'w') for i=1:200; x=rand(1); y=0.7*rand(1) + 3*x; fprintf(f, '%g %gn', x, y); end fclose(f)
I, Berland, the copyright holder of this work, hereby release it into the public domain. This applies worldwide.
In case this is not legally possible: I grant anyone the right to use this work for any purpose, without any conditions, unless such conditions are required by law.
Legend: (cur) = this is the current file, (del) = delete this old version, (rev) = revert to this old version. Click on date to download the file or see the image uploaded on that date.
(del) (cur) 20:57, 25 June 2007 . . Berland . . 600×480 (20,506 bytes) ({{Information |Description=Illustration of linear regression on a data set. |Source=self-made in Gnuplot. |Date=24 June 2007 |Author= Berland }} ==Gnuplot source code== set terminal svg fname "Helvetic)
(del) (rev) 18:56, 24 June 2007 . . Berland . . 600×480 (19,801 bytes) ({{Information |Description=Illustration of linear regression on a data set. |Source=self-made in Gnuplot. |Date=24 June 2007 |Author= Berland }} ==Gnuplot source code== set terminal svg fname "Helvetic)
File links
The following pages on the English Wikipedia link to this file (pages on other projects are not listed):
Generally, regression is related to moving backwards, and the opposite of progression. ... The correct title of this article is . ... Generally, regression is related to moving backwards, and the opposite of progression. ... The correct title of this article is . ...
In statistics, linear regression is a regression method that models the relationship between a dependent variable Y, independent variables Xp, and a random term ε. The model can be written as where β1 is the intercept (constant term), the βis are the respective parameters of independent variables, and p is the... In statistics, regression analysis examines the relation of a dependent variable (response variable) to specified independent variables (explanatory variables). ...
Feeds |
Contact