HP 50G, Руководство пользователя

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Page 18-57
Multiple linear fitting
Consider a data set of the form
Suppose that we search for a data fitting of the form y = b
0
+ b
1
⋅
x
1
+ b
2
⋅
x
2
+
b
3
⋅
x
3
+ … + b
n
⋅
x
n
. You can obtain the least-square approximation to the
values of the coefficients b = [b
0
b
1
b
2
b
3
… b
n
], by putting together the
matrix X:
_ _
_ _
Then, the vector of coefficients is obtained from b = ( X
T
⋅
X )
-1
⋅
X
T
⋅
y , where y is
the vector y = [y
1
y
2
… y
m
]
T
.
For example , use the following data to obtain the multiple linear fitting
y = b
0
+ b
1
⋅
x
1
+ b
2
⋅
x
2
+ b
3
⋅
x
3,
x
1
x
2
x
3
… x
n
y
x
11
x
21
x
31
… x
n1
y
1
x
12
x
22
x
32
… x
n2
y
2
x
13
x
32
x
33
… x
n3
y
3
. . . . .
. . . . . .
x
1,m-1
x
2,m-1
x
3,m-1
… x
n,m-1
y
m-1
x
1,m
x
2,m
x
3,m
… x
n,m
y
m
1 x
11
x
21
x
31
… x
n1
1 x
12
x
22
x
32
… x
n2
1 x
13
x
32
x
33
… x
n3
. . . . .
. . . . . .
1 x
1,m
x
2,m
x
3,m
… x
n,m