stats::linReg
-- linear
regression (least squares fit)stats::linReg
(data)
returns the least
squares estimators [a, b] of a linear relation y = a +
b*x between data pairs.
stats::linReg([x1, x2, ..], [y1, y2, ..])
stats::linReg([[x1, y1], [x2, y2], ..])
stats::linReg(s <, cx, cy>)
stats::linReg(s <, [cx, cy]>)
x1, x2, .. |
- | statistical data: arithmetical expressions. |
y1, y2, .. |
- | statistical data: arithmetical expressions. |
s |
- | a sample of domain type stats::sample . |
cx, cy |
- | integers representing column indices of the sample
s . Column cx provides the data x1, x2,
.. , column cy provides the data y1, y2,
.. . |
a list [a, b]
of arithmetical expressions representing
the offset and the slope of the linear relation. FAIL
is
returned, if these estimators do not exist.
cx
, cy
are optional,
if the data are given by a stats::sample
object containing only
two non-string columns. Cf. example 2.stats::reg
.We calculate the least square estimators of four pairs of values given in two lists. Note that there is a linear relation y = 1 + 2*x between the entries of the lists:
>> stats::linReg([0, 1, 2, 3], [1, 3, 5, 7])
[1, 2]
Alternatively, the data may be specified by a list of pairs:
>> stats::linReg([[0, 0], [1, 3.3], [2, 4.8], [3, 6.9]])
[0.42, 2.22]
We create a sample consisting of one string column and two non-string columns:
>> stats::sample([["1", 0, 0], ["2", 10, 15], ["3", 20, 30]])
"1" 0 0 "2" 10 15 "3" 20 30
The least square estimators are calculated using the data columns 2 and 3. In this example there are only two non-string columns, so the column indices do not have to be specified:
>> stats::linReg(%)
[0, 3/2]
We create a sample consisting of three data columns:
>> stats::sample([[1, 0, 0], [2, 10, 15], [3, 20, 30]])
1 0 0 2 10 15 3 20 30
We compute the least square estimators for the data pairs given by the first and the second column:
>> stats::linReg(%, 1, 2)
[-10, 10]
We create a sample of three columns containing symbolic data:
>> stats::sample([[x, y, 0], [2, 4, 15], [3, 20, 30]])
x y 0 2 4 15 3 20 30
We compute the symbolic least square estimators for the data pairs given by the first and the second column. Here we specify these columns by a list of column indices:
>> map(stats::linReg(%, [1, 2]), normal)
-- 2 -- | 13 y - 68 x - 5 x y + 24 x - 28 2 x y - 5 y - 24 x + 84 | | --------------------------------, ----------------------- | | 2 2 | -- 2 x - 10 x + 14 2 x - 10 x + 14 --
stats::sample
.