Table 5 LASSO method applied to the full model, \({Y}_{{X}_{i1}{X}_{i2}{X}_{{i}_{3}}{X}_{{i}_{4}}{X}_{{i}_{5}}}\), for variable selectiona.

From: Factorial design analytics on effects of material parameter uncertainties in multiphysics modeling of additive manufacturing

 

Variable

Regression coefficient

Confidence interval of estimate

1

(Intercept)

1.05840E−01

 

2

PA

2.65950E−02

[2.6481E−02, 2.7403E−02]

3

λ

−1.74210E−03

[−2.5763E−03, −1.6261E−03]

4

μ

−6.21710E−04

[−1.2434E−03, −5.1081E−04]

5

γ

0

[−1.1174E−04, 1.5449E−04]

6

− dγ/dT

0

[−1.3260E−04, 1.7679E−04]

7

PA: λ

0

[−1.9592E−04, 1.6435E−04]

8

PA: μ

1.13830E−04

[−4.3454E−05, 3.1418E−04]

9

PA: γ

0

[−1.3641E−04, 1.6228E−04]

10

PA: − dγ/dT

0

[−1.5428E−04, 1.0928E−04]

11

λ: μ

−5.64980E−05

[−1.8704E−04, 5.5667E−05]

12

λ: γ

−3.73220E−05

[−1.6863E−04, 9.2135E−05]

13

λ: − dγ/dT

−2.23930E−04

[−4.4786E−04, −9.0059E−05]

14

μ: γ

0

[−2.1030E−04, 1.4835E−04]

15

μ: − dγ/dT

0

[−1.8330E−04, 9.5482E−05]

16

γ: − dγ/dT

0

[−1.5408E−04, 1.7311E−04]

17

PA: λ: μ

0

[−9.0821E−05, 1.2955E−04]

18

PA: λ: γ

0

[−1.7375E−04, 1.5250E−04]

19

PA: λ: − dγ/dT

3.35860E−04

[2.1058E−04, 6.7172E−04]

20

PA: μ: γ

0

[−1.1278E−04, 1.5428E−04]

21

PA: μ: − dγ/dT

0

[−1.6792E−04, 1.3970E−04]

22

PA: γ: − dγ/dT

0

[−1.4926E−04, 1.1707E−04]

23

λ: μ: γ

0

[−1.1622E−04, 1.5245E−04]

24

λ: μ: − dγ/dT

0

[−1.8964E−04, 1.6005E−04]

25

λ: γ: − dγ/dT

0

[−1.6836E−04, 1.3746E−04]

26

μ: γ: − dγ/dT

0

[−1.6794E−04, 1.3532E−04]

27

PA: λ: μ: γ

0

[−1.2429E−04, 1.1270E−04]

28

PA: λ: μ: − dγ/dT

0

[−1.0911E−04, 1.6172E−04]

29

PA: λ: γ: − dγ/dT

4.74000E−04

[3.2954E−04, 9.4800E−04]

30

PA: μ: γ: − dγ/dT

0

[−1.3084E−04, 1.1765E−04]

31

λ: μ: γ: − dγ/dT

7.16360E−04

[5.6841E−04, 1.4327E−03]

32

PA: λ: μ: γ: − dγ/dT

0

[−1.4869E−04, 1.4495E−04]

  1. aA bootstrap size of 500 is used to estimate the regularized regression coefficients with the corresponding 90% confidence intervals for the bootstrapped estimates.