Graphics Programs Reference
In-Depth Information
Similar to classic regression, the regression line passes through the data cen-
troid defi ned by the sample mean. We can therefore compute the second
regression coeffi cient
b
0
(the
y
-intercept),
using the univariate sample means and the previously computed slope
b
1
.
Let us load the age-depth data from the fi le
agedepth.txt
and defi ne two
variables,
meters
and
age
. It is ssumed that both of the variables contain
errors and the scatter of the data can be explained by dispersion of
meters
and
age
.
clear
agedepth = load('agedepth.txt');
meters = agedepth(:,1);
age = agedepth(:,2);
The above formular is used for computing the slope of the regression
line
b
1
.
p(1,1) = std(age)/std(meters)
p =
6.0367
The second coeffi cient
b
0
, i.e., the
y
-axis intercept can therefore be com-
puted by
p(1,2) = mean(age) - p(1,1) * mean(meters)
p =
6.0367 -2.9570
The regression line can be plotted by
plot(meters,age,'o'), hold
plot(meters,polyval(p,meters),'r')
This linear fi t slightly differs from the line obtained from classic regres-
sion. It is important to note that the regression line from RMA is
not
the
bisector of the angle between the
x
-
y
and
y
-
x
classical linear regression
analysis, i.e., using either
x
or
y
as independent variable while computing
the regression lines.
