Research of Disturbance in Model of Linear Regression Estimated According to Criteria of Least Squares

APPENDIX o b s 1 a = - 5 x = 1 .2 9 у = 1 1 .1 х0 = 1.630 ... : 6 ... 3 2 --- --- ---: / = 24.13 6 х - 16.060 2 9 --- --- --- --- : 4 ------- : R = 0.738 » у 7 * 2 6 ---S _____________ ; 2 --- --- í ________________i

♦ X

i

*

я

23 --- --- i 0 ________ »__________________________________ * _ J S

2 0 —

y

> ---1

♦

*

:

i

g

♦ - 2 --- . ______________; q. 1 7 ----^ r — *--- i * ♦ 1 4 --- 4 - - 0 --- —--- i

&

11 ---♦.---.--- .--- ---.---j c 5 ‘ 1 1 1 I 1--- !---1--- 1--- !--- 1--- 1---1--- 1---1---1---1---1---1---1--- 1 g -1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2 2.1 0 1 2 3 4 5 6 7 8 9 10 11 12 1 3 1 4 15 16 17

3--

--- _J

g

8

F ig . 1. L in e a r r e g re s s io n m o d e l a n d re s id u e s f o r d is tu r b e d v a r ia b le у w ith d is tu r b a n c e c o n s t a n t a = —5 in c o m p a r is o n w ith L S m e th o d o b s 1 a = - 3 x = 1.29 у = 1 3 .1 xQ = 1.629 Ł ... ... : 6 , ... 2 , 3 2 --- --- I : _ у = 2 2 .7 8 1 x - 13.851 . I S ' 2 9 --- ---, ____________ : 4 --- : ™ R2= 0.752 ♦ " 3 ? I . » * й 2 6 ---______________________ :

_{♦ л#*}

_i

2 _____-________________________

_♦

_♦

-________________i

_:

₈

2 3 ---S Z --- .. ; „ ; 4Ę

.

'

:

0 --- , --- J - H

S

г о - - - , —

♦- - - ;

♦

s .

♦ . ' á r * n О

i ? —

*---í

•

;--- :--- --- \

Г

1 4 --- - --- --- j - 4 --- i 11 -I--- ,---,---,---,---,---t---,---,____ j _g . I 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2 2.1 0 1 2 3 4 5 6 7 8 9 1011 12 13 14 1 5 1 6 1 7 F ig . 2 . L in e a r r e g re s s io n m o d e l a n d re s id u e s f o r d i s tu r b e d v a r ia b le у w ith d i s t u r b a n c e c o n s t a n t a = — 3 in c o m p a r is o n w ith L S m e th o d Ü

obs 1 a = - 1 x = 1 .2 9 у = 15.1 х 0 =1.631 ^3 ... ...6 ... 3 2 --- ! i у = 21 426х - 11.643 4 --- í 2 9 --- ---9---i ♦ R =0.7499 ^ , 2 6 --- --- i 2 --- *---i --- *--- i

i

♦

. I

2 3

---i

0--- .--- i

20---*--- 1

®

*

♦

*

♦

♦ /

»

-2 *--- i

1 7 --- *--- j 1 4 --- *--- j ' 4 !

;

11 I I ! I---!---!--- :--- !--- i —6-I---- 1---- 1---- Г——I---- 1----1----1— !----1---- 1---- 1----!---- 1----!---- 1---- 1----i ^ 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2 2.1 0 1 2 3 4 5 6 7 8 9 10 11 12 1 3 1 4 15 16 17 _; 5*

V>

I

Fig. 3. Linear regression model and residues for disturbed variable у with disturbance constant a = — 1

^

in comparison with LS method

§

J

obs 9 a = - 5 x = 1 .5 3 у = 1 5 xn = 4.608 i >

--- y---

---

я

32 ... 6 ... :...g on y = 2 0 .8 5 1 x -11.009 ш

2

*

1

4---r--- :--- g

R2= 0.6373 ♦ j. : £: 2 6 --- .---f S -

_*

--- i

„

_{í --- *--- ;--- ;}

♦

;

ST

2 3 --- ---'• * * i . • / 4 : 0 ---- *---i --- : 20 ---i

*

--- í * - 2 ________________ I _________________ - __________ Í

17 - -

*--- 'i

14

--- J--- — --- j - * --- j 11 --- 1--- i--- 1--- 1--- i---1---1---ľ---i —6 --- 1----!----1----1----1----1----1--- 1—Ф—I----1----1--- 1----1----1----1----1

1.2 1.3 1.4 1.5 1 6 1.7 1.8 1.9 2 2.1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Fig. 4. Linear regression model and residues for disturbed variable у with disturbance constant a = — 5

in comparison with LS method

obs 9 a = - 3 x = 1.53 y = 1 7 x0 = 4.623 z ľ ľ z z z ľ z ľ z ľ ľ ľ ľ z ľ ľ ľ ľ ľ ľ ľ z z z z ľ z ľ z ľ ľ z r ; 6 ... : 32 - ---: 2g y = 20.810x - 10.821_________________________ ; 4 --- ; ---j R 2 = 0.692 ♦ ^ . . , 6 --- _ 4 ^ ---: 2 — *--- : --- . --- n 23 - — j o • — --- 4--- i 2 0 --- , ♦--- i * . í? ♦ ♦ —9 ---*_______________ ; ся 1 7 --- ^ ^ ---í ♦ S 1 4 --- í - 4 --- • --- i & 2> 11 --- I--- 1--- 1--- 1--- 1--- 1--- 1--- !--- i —6 --- 1--- 1----1----1--- 1--- 1----1--- 1--- 1--- 1----!--- T--- I----1----1----1--- i ^ 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2 2.1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 1 5 1 6 17 »

c

or

H

Fig. 5. Linear regression model and residues for disturbed variable у with disturbance constant a = — 3

|

m comparison with LS method

J.

3 obs 9 a = -1 x = 1.53 y = 1 9 xn = 4.700 о

"

г—--- га

...

6 ...,

“

3 2 --- \ 2, y = 2 0 .7 6 9 x - 10.633 4 --- i 2 9 ---, --- : ♦ a 26 R 2 = 0.730 * ^ _____________

j

2 ___________ *

_____________

«

______

I Ę

♦

*

*

♦

*

-ł

2 3 --- г ^ < ---í 0 — »_______________________________________ . _____j Ч 2 0

---;--- —

*———

--- ;

*

»

♦

и

• * ♦ - 2 --- --- » --- *--- ; o' 1 7 — • ---í : ♦ i p 1 4 --- i - 4 --- i 1 1 ^ 1 1 ' 1 1 >--- 1---1 “ 6 --- 1--- 1---1--- 1--- 1--- 1---1--- 1---1--- r---- T---1--- 1---1--- 1--- 1--- 1 1.2 1.3 1 4 1.5 1.6 1.7 1.8 1.9 2 2.1 0 1 2 3 4 5 6 7 8 9 1011 12 13 14 15 16 17

Fig. 6. Linear regression model and residues for disturbed variable у with disturbance constant a = — 1

obs 9

a =

1

x =

1.53

y= 21

xn

=

4.476

... ... ... ... ... ... . Is-T— ♦ . C D - Ю ♦ C O ♦ - C N ♦ - ^ ♦ . о < » - C D ♦ 0 0 ♦ r^. ♦ C D ♦ Ю 4 ♦ C O ♦ C N J T _ o CD -3 C N J С 7 1

Fig. 8. Linear regression model and residues for disturbed variable у with disturbance constant

in comparison with LS method

obs 9

a = 5

x = 1.53

y = 25

x0 = 4.573

31 ... ;

6 .... ...

... ~...i

y = 2 0 .6 4 6 x - 10.068 29 --- 5--- , ---I 4 --- _ --- : 27 R = 0.7015 « j f_____________ i • ♦

^--- *--- »

i

25 ^ „ > r ♦ * ♦ 2 3 ---i

_{r z i}

_i

0 ■ — --- s--- i

_*

_:

_!Я

2 1 ---1 o _________________________ í _____________________ i S 1 9 --- . y C *---

j

Z * I I 17 - * ' Í 1 cr

♦ •

!

S,

-I--- 1--- 1--- í--- 1--- !--- 1--- 1--- 1--- i -6-1--- 1----1----i----1----1--- 1----1--- ,--- ,----,----,----1----,--- ,----,----f--- j 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2 2.1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 S" ---_ _ --- --- t í

---

*i

_tr

g

Fíg. 9. Linear regression model and residues for disturbed variable у with disturbance constant a = 5

n

in comparison with LS method

3

obs 16

a = 1

x = 1.84

у = 29.7

x0 = 1.461

g.

—--- ---

--- --- ---

О

31 £■■... ...I 6 1 : О y = 2 1 .5 7 7 x - 11.749 . i ^ 2 9 --- -— : 4 --- -—---I S t 2 7 ______R 2 = 0 ™ ________ ^ _____________ j ‘ g

jT

■

2 --- ---*---*---_ _ !

4

2 5 --- --- i : ;

* 1

s 2 3

--- v

_{♦ / ♦}

f ---;

_;

°-—---»—

_-

_Se

2 1 --- --- ,

_2

________ : _______ ; i -1 9 --- : * . f 1 7 --- í --- í --- j 15 i--- 1--- '--- 1--- 1--- 1--- i--- 1--- i - 6 --- r— i— i— ,— ,— ,— i— ,— ,— i— i— ,— ,— ,— ,— .,__ j 1.2 1.3 1.4 1.5 1 6 1.7 1.8 1.9 2 2.1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 1617

Fig. 10. Linear regression model and residues for disturbed variable у with disturbance constant a = 1

in comparison with LS method

obs 16

a = 3

x =1.84

у = 31.7

x0 = 4.622

^

31 ... ... ;

6

... ...

... !

20 y = 2 3 .2 3 3 x - 14.171________________________ : ; R 2 = 0.745 X Í ______________________________________________________ • --- i o ________ ♦ _____________________________________________ Í 2 5 --- --- * » * ^ 2 3 --- Ж - --- i 0 1

♦ / *♦

*

♦

2 1

--- !

rj

.

S ♦ ♦

*

:

1 9 ---. ■ / . --- i . ♦ 1 7 — 5 í

15 --- ’--- 1---’---1--- --- '---1--- I--- i - 6 - 1 --- 1--- i--- 1--- 1--- i--- 1---1---1--- 1--- 1--- 1--- 1--- I--- 1--- T---T---i <

1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2 2.1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 1516 17 §

________________________________ ____ _______________________________СГ

I

Fig. 11. Linear regression model and residues for

disturbed variable у with disturbance constant a = 3

^

in comparison with LS method

<g

Я

obs 16

a = 5

x = 1.84

y = 3 3 .7

x0 = 1.4621

>

... ...

~

--- ---

§

31 --- — __________________ _ j 6 ... - ... í on y = 2 4 .8 8 9 x - 16.592--- — j » ' j --- ---jr * --- - 4 --- --- — --- " • ę 2 7 - R = 0 -7 3 2 ______♦ V T - I ] . I 2 5 ____________________ ^ 2 ' “ T ♦ • • I

23 --- - Л -rĹ--- i

0 —

i

♦ / • ♦

♦

2 1--- —

_{X ♦ ♦}

--- --- •; _ 2_____________________

_*

*

_{♦--- —}

; 1 9 --- I 1 7 --- --- ♦---__i ~ 4 — --- I 1 5 ' ' ' ’--- '--- »--- '--- ’--- i 6 — ,— ,— ,— ,— ,— ,— ,— ,— ,— ,— ,— ,— ,— ,— ,— .— j 1.2 1.3 1 4 1 5 1.6 1.7 1 8 1.9 2 2.1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Fig. 12. Linear regression model and residues for

disturbed variable у with disturbance constant a = 5

obs 1 a = - 5 x = 1.29 у = 1 1 .1 x 0 = 1.630 ... ....- ... ... : 6 ...- ..., 3 2 --- 1 y = 2 4 .1 3 6 x - 16.060 4 2 9 --- ---i 4 ; --- ; 26 ______ * 2 = 0 '738 ___________ i 2 _____ »— I - - ______ T______ ±_______________ i 2 3 --- --- I 0 ---2 0 --- , ---. --- 1 * £ ♦

. u S *

- 2 --- • --- i 8 1 7 --- --- * — --- 1 * * I 1 4 --- — ___________________________________ I ---j S-^ 4—— * 1 I I I I--- 1---1---1--- i —6 --- 1--- 1--- 1--- 1--- 1--- i--- 1--- 1--- !--- 1--- 1--- !--- 1--- !--- !--- i---i ^

1.2 1.3 1.4 1.5 1.6 1.7 1 8 1.9 2 2.1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

g

---—--- ---

c

o*

F ig. !3 . L in e a r regression m od e l and residues fo r d istu rb e d v a ria b le

у

w ith distu rb a n ce co n sta n t

a =

— 5

in co m p a riso n w ith LS m eth o d - .

3 obs 1 a = -1 x = 1.29 у = 1 5 .1 x 0 = 1.631 &

~

"

---

--- —--- ---

n

... ... ... ... ...;

6 ... ... .

“

3 2 --- - ! 2, 29

У=

21,4 2 6 x - 11.643_______________________ 4 ____________________________________________ j g; = 0.7499 *

^

2 _____ _i _____________________ j §

'

ф

♦

23

г х % - - -

о - - - .-- - - i

4

2 0 --- , . --- • ♦ I • - 2 ---L________________*_________ : S ’

17 — ^

*--- i

:

.

i

p 1 4 --- --- i - 4 ---

\

' ' ' ' 1 ' 1

—>

’ - 6 ---1----1--- 1----1----1--- 1--- 1----Г--- 1----1----1----1—-i----1--- 1----1--- i 1 2 1 3 1.4 1.5 1.6 1.7 1.8 1 9 2 2.1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

F ig. 14. L in e a r regression m od e l and residues fo r d istu rb e d v a ria b le у w ith d istu rb a n ce co n sta n t

a = —

1 in co m p a riso n w ith LS m ethod

obs 9 a = - 3 x = 1.53 y = 17 x0 = 4.623 ... - ... , 6 ... ... ... .... : 3 2 --- ---

j

29 y = 20.81 Ox - 10.821___________ ____________ j 4 --- i --- j R 2 = 0.692 ♦ ^ j _________ í _________________

-

_______________ !

2 6

.

--- I

2

П

2 3 --- j 0 ---*--- j

20 —

• --- i

-2____ :____1________ ^ ______i

1 7 --- ♦ ♦--- 1 1 4 j 4 --- * --- j

11 I--- i--- 1--- 1--- T--- !--- I--- 1--- 1 —6 -I----1----r— T----1----1----I----1----1----'--- 1----1----1----p----!---- 1----1----i ^ 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2 2.1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 1 4 1 5 16 17 g '

I

Fig. 15. Linear regression model and residues for disturbed variable у with disturbance constant a = — 3

5;

in comparison with LS method

<§

a

»-»

obs 9 a = 1 x = 1 . 5 3 у = 21 Xq = 4.476 > Z Z Z ' ľ - . . ľ T I " . Z ľ ľ ľ ľ ľ ľ Z ľ . , 6 — I „ n ‘ y = 2 0 . 7 2 8 x - 10.445 j 4 _________________________________________________ j ® 2 9 --- ---щ---í ♦ о-2 7 R = 0 7 ^ --- -- / --- j 2 ____________________♦________________ j F 2 5 ---♦ --- -! ♦ * ♦ : 23 --- ---j

_{♦ / *}

° — --- • ---*--- I

_♦

_.

_•

2 1 --- y f --- i - 2 --- *--- i 1 9 --- ,* / % --- *--- i ♦ 17 - 1 --- j ^ --- ] 15 1--- !--- T--- 1--- I--- T--- 1--- 1--- i - 6 ----1--- 1----1--- 1--- 1--- 1--- 1----1----1----1----1----1--- 1----1----1--- 1----i 1.2 1.3 1.4 1.5 1.6 1.7 1 8 1.9 2 2.1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Fig. 16. Linear regression model and residues for disturbed variable у with disturbance constant a = 1

in comparison with LS method

obs 16 a = 3 x = 1.84 у = 31.7 x 0 = 1.4622 31 j - ... ...4...: 6 ] ... •; OQ y = 2 3 .2 3 3 x - 14.171 --- — — —---i 4 ---

-2 7 R = 0 .7 4 5 _________ ♦ У х ______________ i ♦ ф 2 5 --- . Ж Г - - 7 - : 2 — ^ --- ; --- - --- j 2 3 --- _________________________ i 0 ■ — i --- — --- j » y ľ * * ! * ' •B 2 1 ---— --- --- : 0 ♦ £ . / • * “ 2 *---i a 1 9 --- ♦ / --- : ♦ ♦ * 1 7 ---

S -

--- i --- i --- í S-15 -I

---’---T

---,---,---,---,---

t

---T

---

;

- 6l - ...- r.

... j 2 . 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2 2.1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 1516 17 ~

— ---

L---—---

B

•4

cr

F ig 17. L in e a r regression m odel and residues fo r d istu rb e d va riab le у w ith d istu rb a n ce co n stan t

a

= 3 in co m parison w ith L S m ethod

5' 3 obs 16 a = 5 x = 1.84 y = 33.7 x n = 1.4621 g.

“

--- --- —i

---31 ... 6 ] ... ~~... ...- ... : О 7Q у = 24.889x -1 6 .5 9 2 j • ! ^ „ R 2 = 0.732 . n 2 7

---

---

2

.

*__________________

I

4

2 5 --- --- . j 3 2 3 --- --- 0 --- --- j *§

♦ X %

♦

и

2 1 --- --- _ 2 ___________________ * j 5-*

/

♦

*

■ 3 1 9

---

:

S

.

---

.

Г

1 7 ---r b Č ---i---- --- i 15 ---I---.---.---.--- .--- .---.--- .--- i - e l - ... ... 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2 2.1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

F ig. 18. L in e a r regression m odel and residues fo r d istu rb e d va riab le у w ith d istu rb a n ce co n stan t

a =

5

obs 1

с = -0.2 x =1.09

у =16.1

X

q

= 1.598

g

32 --- — ---; 4]--- — --- *---i y = 17.202»-4 .8 7 1 ________________________________________________ 2 9 --- --- ф---: O --- : R 2 = 0.700 ♦ 2 - - * ---t---* — 2 6 --- --- í 1 ____________________ í __________________ ♦ ____________________________________________ * * ♦ 2 3 ---v / Ч i 0 ---j 2

° ---*

i

_„1

:

i

^

- »---

t

*

T-1 4 --- -j . 4 --- í --- ; 11 ---1---!---1---1---1---1---1--- 1---1---1---i —5 ---1---1--- 1--- 1--- 1---1--- 1--- 1--- 1--- 1 i---:--- 1--- 1---1--- . 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2 2 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 2p

_o

_____________________________________________ ______________________________________________________ 5П

S

Fig. 19. Linear regression model and residues for disturbed variable у with disturbance constant с = — 0.2

^

in comparison with LS method

ere

5

obs 1

с = -0.05

x = 1.24

y=16.1

xn = 1.620

>

--- ---

...—... - ...

Ш --- §

5 ... - ...: P 3 2 --- 4 --- ---; S3 y = 1 9 .9 8 7 x -9 .3 0 4 « e

29

--- ---

I'

F

26 --- 1 - ^ --- ♦--- ---2 3 ---

- S

f

---

0 - *

--- •---2 0 ---*--- - i ---— - — ♦— « : ---1 7 --- ^ ^ - 3

---*---*---14---^

---11 --- ,---,---,---1--- ,--- ,---,---,---,---,---i - 5 — .— .— .— >— ,— .— i— ,— i— -— ,— ,— .— ,— ,— ,— 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2 2 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Fig. 20. Linear regression model and residues for disturbed variable у with disturbance constant с = —0.05

in comparison with LS method

obs 9 с = -0 .1 5 x = 1 .3 8 у = 20 x0 = 1.798 ... ...- ... 5 ... - ...- ... 31 --- --- --- i y = 20.028X - 9.243 4 ---29 --- *---i 3 ___________________________________ í _______i 27 ---« = 0 -735---*--- ---1 2 _______________________________ . ________________ j

У

i

‘

•

2 5--- 1 1 --- --- *--- *--- *• 2 3 --- --- í 0 . ---*---♦ / *♦ _

л

.

_ 1

_____________________________________________ JO 2 1 ______________ •—/*—____________________________

_:

_л

.

_*

_«

♦ ra

_v.

♦ v * ♦ —2 ---• --- ; g 1 9 --- --- i _{/ - 3 --- —---j --- *---} , í_o 1 7 ---í ---; __________________________________________ ; t r f » o 15 --- ,--- ,--- ,--- ,--- ,--- ,--- ,--- ,--- i - 5 -J— ,— , i ■ ■■ ,— y - ^ - , — r - , — r -, , ,— ,— i 1.2 1.3 1.4 1.5 1.6 1.7 1 8 1.9 2 2.1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 B'

- - - -—

- - - -- - -

S

_*1

cr

i

Fig. 21. Linear regression model and residues for disturbed variable у with disturbance constant с = —0.15 |

in comparison with LS method _.

3

obs 9 с = -0 .0 5 x = 1.48 у = 20 xQ = 4.900 a. ---— — --- --- --- re 31 ... - ... v... ; 5 i ... ... ...; о y = 2 0 . 7 5 9 x - 10.49 i 4 --- _ 29 - i --- ---, ---i = fT = 0.7483 . . J --- — a 2 7 --- ' у / --- j--- 2 --- , --- . --- --- ES 2 5 --- -- -S --- ! 1 --- 5--- *--- *--- — 3 2 3 ---1 0 — --- Щ--- *--- 1 2 1 ---5 ^ — --- i --- 5 ^---5--- o ♦ / • - 2 --- *--- В 1 9 --- --- :--- - 3 ---? . ---i--- - 4 --- --- : ^ 5 I ' I I I I ! 1 - 5 - ---- 1 I ---- !' ■ ■ I----1----1----r— l----1----1--- 1----1--- 1--- 1----1----: 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2 2.1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 1 7

Fig. 22. Linear regression model and residues for disturbed variable у with disturbance constant с = —0.05

obs 9

с = 0.05

x = 1.58

y = 20

xn = 1.304

CT>

--- --- У---

--- ---

N)

31 ... ... ... - ...

5 ... :

y = 20.473X - 10.179 4 --- j OT R 2 = 0.7248 ” Z 3 --- ---^ 27 — --- *--- —*■--- , 2 ___________ , __________________ ♦________________ : 2 5 --- ♦ --- ■ -i--- *_______ . _______ í _____________________ 2 3- - --- __________________________j 0 — щ--- *---i

• X *♦

1

21--- ______________________ J

--- *--- ;--- *--- :

♦ ♦ - 2 ---a ____________ í _____________

19—

---__________________

t

* .

n

1 7 —

x

*---

_ 4 ---;

15 ■* T--- ’--- ’--- T ’--- T--- T--- T--- i - 5 4— ... ■ ■ , . , i £ 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2 2.1 0 1 2 3 4 5 6 7 8 9 1011 12 13 14 15 16 17 5 ' --- — --- _ --- --- --- _ ___________________________________________________________________ 09

4

Fig. 23. Linear regression mode] and residues for disturbed variable у with disturbance constant с = 0.05

in comparison with LS method

tg

о

- i

obs 9

с = 0.15

x = 1.68

у =20

x0 = 1.421

1

^ ... -... ... s ...-...; § 29 у = 19-199x - 8.336 ; 4 ---, ---j И 2 7 - r 2 = 0 6 6 7 ♦ Z Z : I --- *--- 1 I 2 5 - 1 _________ j 1 * ' Z > -23 ---& Ć --- I 0 — --- --- ; 2 1 --- ; _ 1 --- *--- í --- . --- • S ' ♦ ♦ _ 2 --- :

■

9— •; -x;—

1

---i--- J--- .— •_____

17

1---i--- i --- • --- 1

^ ---- 1--- 1--- 1--- 1---1---1---1--- r---1--- - 5 ---1--- r— ----1----1----1---1----1--- ,----1----1----1----1----,--- ,--- ,----1 1 2 1.3 1 4 1.5 1.6 1.7 1.8 1.9 2 2.1 0 1 2 3 4 5 6 7 8 9 1011 12 13 1 4 1 5 1 6 17

Fig. 24. Linear regression model and residues for disturbed variable у with disturbance constant с = 0.15

in comparison with LS method

obs 16

с =

0.1

x

=1.94

у

=

28.7

xn =

1.465

S

8

8

I43

u

г

сл 4 3

a

i

i

i

i

1

2

1

в

С

о

•я

с

□

ЫЭ

Е

i

!

О

.8

ГА

О

II

О

Fig. 26. Linear regression model and residues for disturbed variable у with disturbance constant

in comparison with LS method