Titel_SS06

information matrix 2.45
informed preferences 13.4
inherent natural variability 2.18
inspections 12.1, 12.5, 12.6, 12.7, 12.8,
12.9, 12.15, 12.29, 12.30
instantiation 10.4
intensity 2.29
interquartile range 2.16
interval estimates 2.42

J

Jensen’s inequality 2.26
joint
central moment 2.26
cumulative distribution function 2.26
probability density function 2.26

K

kurtosis 2.11

L

Life
Expectancy Index (LEI) 13.11, 13.12, 13.13
cycle 13.22
Quality Index 13.1, 13.14, 13.15
likelihood 1.7, 2.6, 12.14, 12.19, 12.20,
12.22, 12.25, 12.28, 12.30
limit state function 6.1, 6.2, 6.3, 6.4, 6.6, 6.7, 6.8, 6.9,
6.10, 6.12, 6.15, 6.17, 6.20, 12.1,
12.10, 12.11, 12.13, 12.27
load 7.1, 7.2, 7.3, 7.4, 7.5, 7.6, 7.8, 7.9, 7.10,
7.11, 7.12, 7.13, 7.14, 7.15, 7.16, 7.20
Lognormal Distribution 2.25

M

median 2.9
Method of Maximum Likelihood 2.43
Method of Moments 2.42

mode 2.9

Model

building 2.37

Selection 2.39

uncertainty 2.18, 7.19, 7.20

moments 2.22

Monte Carlo 6.2, 6.3, 6.17, 6.18

N

n-dimensional cumulative distribution function 2.27

net present value 13.22

Normal

probability distribution 2.24

process 8.1, 8.4

tail Approximation 6.12

numerical summaries 2.9

O

observations 2.8

optimization 11.1, 11.6, 11.7, 11.8, 11.9, 11.10, 11.11,

13.1, 13.13, 13.18, 13.22, 13.23

out-crossing 8.1, 8.5, 8.6

rate 8.1, 8.4, 8.6

outside value 2.16

P

parallel system 9.3, 9.4, 9.5, 9.8, 9.9

parameters 2.22

partial safety factor 6.14, 6.16, 11.2, 11.3, 11.4,

11.6, 11.11

physical uncertainties 2.20

point estimates 2.42

point in time 2.28

Poisson

counting process 2.29

process 8.1, 8.3, 8.4, 8.7

posterior

analysis 3.5, 3.6, 3.11,9.18, 10.10, 12.1, 12.11,

12.19, 12.20, 12.21, 12.22, 12.24, 12.25

probability 2.6

I.3