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Subject index
Volumes 1–5, 2018
Volume 5, Issue 4 (2018), pp. 551–559
https://doi.org/10.15559/18-VMSTA54SI
Pub. online: 14 January 2019      Type: Subject Index     

Published
14 January 2019

The number with dot before page numbers indicates volume number.
A
Aalen counting processes 2.8
ADF regression 2.71, 2.77
ADF statistic 2.57, 2.58, 2.72, 2.77
Adjusted least squares (ALS) estimator 3.21, 3.24
Adjusted rand index (ARI) 5.21
Admissible coverings 3.120
Anticipating stochastic integral 2.34
AR processes 4.383, 4.394
ARMA processes 2.52, 4.382, 4.384, 4.388, 4.394
Asymptotic additivity (AA) 4.248
Asset price
 process 2.239, 2.417
 volatility 2.356
Autocovariance matrix 2.60
Autoregression 2.56, 2.61, 2.70, 2.76, 3.60, 3.68
Attributable proportion (AP) 4.110
B
Backward stochastic differential equations (BSDE) 4.353
BDG inequality 4.33, 4.34, 4.44, 4.47, 4.48, 4.59
Bernstein function 5.358
Bessel process 3.224–3.227, 3.230, 5.448
Bifractional Brownian motion 4.16
Bivariate VAR model 2.61
Bonferroni inequality 4.73
Borel probability measure 4.255
Brownian motion 2.31, 2.33–2.35, 2.108, 2.111, 2.186, 2.189–2.197, 2.234, 2.264, 2.328, 4.16, 4.26, 4.190, 4.193, 4.195, 4.308, 4.311, 4.316, 4.355, 5.54, 5.57, 5.58, 5.60, 5.70, 5.71, 5.76, 5.83, 5.115, 5.146, 5.147, 5.416–5.418, 5.447, 5.448, 5.485, 5.492, 5.494, 5.510
 fractional 4.16, 4.17, 4.21, 4.192–4.194, 5.100, 5.101, 5.104, 5.105, 5.298, 5.416, 5.417, 5.420, 5.431
 standard 2.31, 2.41, 2.42, 4.17, 4.191, 4.308, 5.120, 5.147, 5.148, 5.417
Brownian sheet 2.288–2.293
Burkholder inequality 3.9
C
Càdlàg progressively measurable processes 4.29
Cantor distribution 4.412
Cap style cliquet option 5.91, 5.96, 5.335
Characteristic triplet 1.50, 1.52, 1.59, 1.60
CIR process 3.2, 3.12, 5.100, 5.114, 5.115, 5.117
 distribution 5.116
 fractional 5.100, 5.101, 5.103, 5.105
Circulant matrix 3.183, 3.347
Circular bivariate Cauchy distribution 4.80–4.82, 4.88
Cliquet option 5.81, 5.82, 5.91, 5.92, 5.96, 5.317, 5.318, 5.325, 5.326, 5.331, 5.333
 price 5.82, 5.87, 5.91–5.96, 5.318, 5.319, 5.324–5.328, 5.331–5.333, 5.335
Cointegrated sequences 3.60, 3.68–3.70, 3.72, 3.76
Cointegration 2.52, 2.62–2.64, 2.87
 test 2.63
Compensated Poisson random measure 4.26
Compound Poisson process 2.2, 2.6, 4.165, 4.168, 4.173, 4.184, 4.317, 5.172, 5.176, 5.303, 5.305, 5.308, 5.315, 5.322, 5.510
Conditionally Gaussian processes 5.484, 5.485, 5.488, 5.489, 5.495
Confidence intervals (CI) 4.110
Conic section 3.20, 3.21, 3.24, 3.25, 3.27, 3.34, 3.35, 3.40, 3.44
Consistency 2.18, 2.20, 2.82, 2.132, 2.149, 2.163, 2.187, 2.299, 2.301, 2.344, 2.346, 2.352
Constant volatility 2.233, 2.365
Continuous additive functional 2.108
Continuous flow 2.189
Convex random closed set 3.326
D
Daley inequality 3.316
Damped stable processes 2.403
Deterministic volatility 2.356, 2.364, 2.366
Diffusion process 2.252
Dirichlet
 distribution 2.4
 process 2.4, 2.7
 process distribution 2.4
Discounted price process 1.99, 2.236, 2.238, 2.239
Dominating distribution 3.319
Domination sequence 3.319
Doob inequality 2.207, 2.213, 3.7
Double integral 2.140
Drifted Brownian motion 5.447, 5.452, 5.454
Driftless subordinators 5.511
E
Economical processes 3.133
Eigenfunction representation 2.289
Entropy power (EP) 4.245
Entropy power inequality (EPI) 4.238
Equivalent local martingale measure (ELMM) 2.238
Equivalent martingale measure (EMM) 2.238–2.240
Ergodic scaling transformation 1.74, 1.75, 1.78, 1.79, 1.83, 1.87
Ergodicity 1.38, 1.74, 1.79, 1.83
Erlang distribution 4.185, 4.316, 5.511
Error
 distribution 3.52, 5.38, 5.51
 sequences 3.48
European call option 1.96, 1.97, 1.101, 2.235, 2.241, 2.242, 2.246, 2.248, 2.356
 price 2.234, 2.243, 2.355, 2.358, 2.361, 2.364, 2.366
Exponential
 bound 1.169, 1.172, 1.179
 Chebyshev inequality 5.133
 process 5.174, 5.182, 5.185, 5.187
Extinction probability 4.2, 4.4
F
Faithful coverings 3.121
Family of coverings 3.120, 3.121, 3.217
Feller process 2.109–2.114, 2.125
Finite
 Lévy measure 5.319, 5.361, 5.364, 5.368
 symmetric Lévy measures 5.364, 5.365, 5.367
Finite mixture models (FMM) 2.344
Folded Cauchy distribution 4.80, 4.82, 4.85
Folded drifted Brownian motion 5.454
Forecast
 error 2.55, 2.73
 error RMSFE 2.55
 estimation error 2.82
 future 2.52
 horizon 2.61
 methods 2.51
Forecasted value 2.55
Formal information criteria 2.60
Fractional Brownian
 field 1.74, 1.75
 motion 1.74, 1.96, 1.102, 1.103, 1.130, 2.31, 2.33, 2.35–2.37, 2.41, 2.148–2.150, 2.219–2.222, 2.294, 2.334, 3.107, 3.108, 3.112, 3.181–3.184, 3.210, 3.303
 sheet 1.74, 1.75, 1.77, 1.79, 1.91, 1.92
Fractional integral 2.220–2.223, 2.227, 2.229, 2.230
Fractional Skellam processes 4.162
Fredholm
 integral equation 2.148, 2.152, 2.153
 representation 2.288, 2.289, 2.292–2.294
Fuzzy adjusted Rand index (FARI) 5.9, 5.22
Fuzzy Rand index (FRI) 5.22
G
Gamma
 process 4.162, 4.163, 4.165, 5.168, 5.178, 5.182, 5.187, 5.510
 subordinators 4.162, 4.166, 5.514, 5.515, 5.517
Gaussian
 process 1.140, 1.141, 1.144, 2.30, 2.32–2.35, 2.241, 2.267, 2.268, 2.282, 2.292–2.294, 2.310, 2.313, 2.314, 3.108, 3.111, 3.184, 4.194, 5.57, 5.417, 5.483–5.496
 field 5.430
 random matrix 3.48
 stationary process 1.140, 1.183–1.185
Generalized backward stochastic differential equations (GBSDE) 4.25
Generalized inverse Gaussian (GIG) distribution 5.514
GINAR processes 5.58
Gibbs inequality 3.129
Granger causality 2.52, 2.55, 2.61, 2.62, 2.64, 2.82, 2.86, 2.89
Granger causality test (GCT) 2.55
GRETL lag length 2.85
H
Hellinger distance 2.5, 2.394, 2.395
Hermite processes 2.327, 2.332, 2.334, 5.431
Hitsuda representation theorem 2.293
Homogeneity hypothesis 1.203
Homogeneous
 distribution 2.176
 Poisson process 4.413, 4.414, 4.416
Hurst index 1.74, 1.96, 1.103, 1.105, 1.107, 1.108
Hybrid method (HM) 5.6
Hybrid stochastic volatility (HSV) 5.146
I
ID distribution 5.510, 5.511, 5.513, 5.515–5.518
INAR processes 5.54
Information criteria 2.61, 2.64, 2.70, 2.75, 2.76, 2.81
Information matrix 5.232, 5.233
Inhomogeneous renewal risk 2.174, 2.176
 model 2.174, 2.176
Innovation process 2.276
Invariance principle 2.334
Invariant
 density 2.19–2.21
 probability measures 4.256, 4.266
Inverse
 gamma subordinator 5.514, 5.515
 Gaussian
  distributions 5.514
  process 5.510
  subordinators 4.166, 5.510, 5.514, 5.515
 stable subordinators 5.516, 5.517
 subordinators 4.174, 5.451, 5.510–5.512, 5.514, 5.515
Inverse tempered stable subordinators (ITSS) 5.513
Inverse Wishart distribution 2.7
Isonormal Gaussian process 2.33–2.36
Isotropic random
 flight 5.462
 set 3.343
Iterated
 Brownian motion 5.448
 function system (IFS) 4.254
 multivariate forecasts 2.61
 process 5.185
 stochastic integral 2.37
Itô
 formula 1.53, 1.55, 1.59, 1.153
 integral 2.37
K
Karhunen representation 2.289, 2.292
Kato class 2.108–2.110, 2.114
Kernel
 function 5.298, 5.300, 5.302
 representation 2.159
 symmetric 2.291
L
Lack of decrease (LOD) 4.224
Lack of increase (LOI) 4.223
Lack of monotonicity (LOM) 4.224
Lack of negativity (LON) 4.229
Lack of positivity (LOP) 4.228
Lack of sign (LOS) 4.229
Lag length 2.56, 2.60, 2.61, 2.71, 2.76, 2.78, 2.82
 in VAR models 2.60
 selection 2.60
Lamperti transformation 1.74, 1.78
LAN property 1.34–1.39
Laplace exponent 4.95, 4.163, 4.165–4.167, 4.174, 5.177, 5.178, 5.186, 5.511–5.515
Laplace transform (LT) 5.513
Large deviation principle (LDP) 3.96, 3.145, 4.5, 5.486
Least favorable
 densities 3.70, 3.73
 spectral densities 3.71, 3.72, 3.74–3.77
Least squares estimator (LSE) 2.298, 5.191
Lebesgue dominated convergence 3.233
Length vector distributions 3.351
LePage series 3.139, 3.140, 3.239, 3.242, 3.244
Level crossing probability 5.483, 5.495
Lévy
 kernel 1.50, 1.52, 1.59–1.61
 martingale 2.191
 measure 1.37, 1.50, 1.51, 1.59, 1.60, 2.111, 2.125, 2.126, 2.403, 2.404, 2.411, 2.412, 4.163–4.167, 5.88–5.90, 5.169, 5.178, 5.182, 5.185, 5.186, 5.298, 5.322, 5.355, 5.357, 5.358, 5.360, 5.361, 5.364, 5.367, 5.368, 5.371, 5.377, 5.380, 5.381, 5.446, 5.511
 process 2.2, 2.112, 2.126, 2.210, 2.252, 2.402, 2.403, 2.411, 4.163–4.165, 4.169, 5.87, 5.91, 5.178, 5.181, 5.300, 5.301, 5.310, 5.318–5.321, 5.324, 5.333, 5.335, 5.446, 5.510, 5.511, 5.516
 process independent 5.181
 type process 2.112
Lévy driven SDE 1.34, 1.37, 1.38, 1.118
Lévy fractional Brownian field 1.77, 1.78
Linear Lebesgue probability measures 1.4
Linear programming problem (LPP) 2.299
Linear regression 2.297, 2.301, 2.303
Local martingale 2.236, 2.238
Local time 1.110, 1.112
 distribution 1.112
Logistic distribution 2.137, 2.145
Lognormal distribution 5.425
Loss function 3.290
Lundberg inequality 2.175, 2.176, 5.131
Lyapunov condition 1.44, 1.205, 1.206
M
Malliavin calculus 2.30, 2.32, 2.35, 2.166, 2.288, 2.402
Marginal probability measure 5.489
Markov
 binomial distribution 5.212
 process 1.33, 1.34, 1.38, 1.50, 1.53, 1.119, 2.107–2.111, 2.115, 2.165, 2.166, 2.251, 2.252, 2.265, 2.401, 2.402, 2.417, 3.96, 3.100, 3.147, 3.192, 3.224, 3.304, 4.17, 4.18
Martingale convergence theorem 4.262
Maximum likelihood
 estimator 2.17, 2.18, 2.132, 2.163, 3.29, 3.30, 3.35, 3.37, 3.39, 3.52, 3.107, 3.109–3.111, 3.113, 3.270, 3.276, 3.277, 5.6, 5.230
 estimator construction 2.149, 2.150
MB distribution 5.212
Mean squared error (MSE) 5.12
Meixner
 distribution 5.82, 5.84–5.87, 5.90, 5.96
 process 5.82, 5.85, 5.87, 5.91
Mild solution 3.137, 3.139
Minimal martingale measure (MMM) 2.238, 2.241
Minimum Hellinger distance 2.394
Molchan martingale 2.149
Moving average (MA) 2.52
Multifractional Brownian motion 4.16
Multiperiod VAR forecasts 2.61
Multiple
 regression line 2.71
 sclerosis (MS) 4.111, 4.117
 Wiener integrals 2.36, 2.43
Multiplicative process 3.12
Multivariate forecast 2.61
Mutually independent 4.145, 4.170, 4.316–4.319, 5.130
N
Nonlocal porous medium equation (NPME) 5.457
Nonlogarithmic convergence rates 3.2
Nonpositive Bessel process 3.225
Numerical forecasts 2.92
O
Objective option price 1.96, 1.97, 1.101, 1.103, 1.105, 1.107, 1.108
Occupation time option 2.402, 2.404, 2.417
Offspring distribution 4.2, 4.3, 4.5, 4.6
Open set condition (OSC) 3.216
Optimal linear estimate 3.63, 3.66, 3.67
Ordinary least squares (OLS) 2.53, 3.24
 cointegrating regression 2.63
 regression 2.58
Orthogonal regression (OR) 3.24
P
Packing dimension 2.372, 2.373, 2.378–2.384, 2.386, 2.388
Parametrix method 2.412
Partial differential equation (PDE) 5.114, 5.318
Pareto distribution 3.171
Pathwise
 integral 2.36, 2.37
 volatility 2.30
Periodogram 1.181, 1.182, 1.185, 1.186
Permanent insurance policy (PIP) 4.128
Planar Lebesgue probability measures 1.4
Poisson
 point process 2.3, 2.12, 2.13
 process 2.2, 4.162, 4.163, 4.165–4.167, 4.170, 4.174, 4.412–4.414, 4.419, 5.167–5.169, 5.172, 5.177, 5.179, 5.182, 5.185–5.187, 5.319, 5.322, 5.510, 5.511, 5.517, 5.518
 random measure (PRM) 4.26, 5.82, 5.310, 5.319
Policyholder 4.128, 4.129, 4.132–4.136, 4.138, 4.141–4.148, 4.151, 4.153, 4.156, 4.158
Posterior contraction rate 2.2, 2.6, 2.8, 2.9
Predictable processes 4.29, 4.50
Price processes 4.92
Process
 exponential 5.174, 5.182, 5.185, 5.187
 gamma 4.162, 4.165, 5.168, 5.178, 5.182, 5.187, 5.510
 inverse 4.163, 4.173–4.182, 5.168
 inverse Gaussian 5.510
 stable 5.510
 volatility 2.234, 2.240, 2.356
Progressively measurable
 function 4.353
 processes 4.377
Pseudomoments 2.96–2.98, 2.105
Q
QLR statistic 2.58, 2.72, 2.75, 2.79, 2.80
Quantile function 4.290
R
Rand index (RI) 5.21
Random
 convolution 4.67
 distribution 3.213, 3.214, 3.35
 errors 3.49, 3.288
 flights 4.79, 4.82, 5.459, 5.462, 5.464, 5.465
 matrix 3.48, 3.51, 3.52, 3.288, 5.250, 5.274
 measure 4.29
 models 5.459, 5.466
 motion 5.463
 Poisson measure 4.28
 polygons 3.326
 realization 3.49, 3.289
 rectangle 3.359
 regular zonotope 3.362
 set 3.238, 3.325, 3.342, 3.344–3.346, 3.359
 stable noises 5.429
 symmetric body 3.342, 3.343
 symmetric convex set 3.326, 3.327, 3.343, 3.346, 3.357–3.360, 3.362
 walk 4.97, 4.98, 4.316, 5.138, 5.142, 5.462, 5.463
 zonotopes 3.326, 3.327, 3.342, 3.344–3.347, 3.352, 3.357, 3.362
Randomized periodogram 2.31, 2.32, 2.37
 estimator 2.30
Randomized time 5.167
Randomly stopped
 processes 4.91
 sums 3.168
Randomness 4.26
Regression 2.53, 2.55, 2.57, 2.58, 2.63, 2.64, 2.71, 2.72, 2.80, 2.272, 2.299, 2.300
 analysis 2.51, 2.63
 coefficients 2.53, 2.55
 design matrix 2.297
 function 2.58, 5.195, 5.202, 5.203
 line 2.53, 2.71
 model 2.53, 2.58, 2.68, 2.301
 problem 2.269
Regressors 2.55, 2.59, 2.63, 2.64, 2.68, 2.71, 2.347
 vector 2.344
Regular best asymptotically normal (RBAN) estimators 3.31
Renewal
 process 5.517, 5.518
 risk 2.173–2.177
 sequence 5.517
Representation
 integral 2.164
 kernel 2.159
Reproducing kernel 2.290, 2.292, 2.294
 Hilbert space (RKHS) 2.290, 2.292, 5.485
Response
 function 4.95, 4.98
 process 4.94
Restricted Oppenheim expansion (ROE) 4.275
Risk model 2.173–2.176, 2.422, 2.424, 2.426, 2.427
Rosenthal inequality 5.261, 5.271, 5.272
Ruin probability 1.168, 1.169, 1.172, 1.174, 1.175, 2.175, 2.422, 2.429, 4.315–4.318, 4.328, 4.335, 4.341, 4.345, 4.347, 4.348, 5.131, 5.132, 5.136, 5.137, 5.139, 5.141
S
Scaling transformation 1.74, 1.75, 1.78–1.81, 1.83
Semimartingale
 process 2.236
 quadratic variance 2.30
Series expansion 2.288, 2.294
Shannon differential entropy (SDE) 4.234
Shannon entropy (SE) 4.233
Significance level 2.57, 2.71, 2.72, 2.75, 2.77, 2.79, 2.80, 2.82, 2.83, 2.86
Skellam
 distribution 4.164
 process 4.162–4.164, 4.166, 4.170, 4.171, 4.177, 4.181, 4.182
Skewed offspring distributions 4.410
Skorokhod
 approach 3.270
 conditions 3.271
 integral 2.34, 2.36, 2.37
 selection theorem 3.306, 3.307
Sociological data analysis 1.196, 1.203
Solution
 pathwise uniqueness 3.15, 3.274, 3.304
Spectral
 densities 1.182–1.186, 2.268, 2.270, 2.272, 2.273, 2.276, 2.284, 3.60, 3.62, 3.66, 3.68, 3.70–3.77
 function 3.61
Spurious regression 2.57
Stable
 convergence 5.299, 5.300, 5.302–5.304, 5.307
 process 3.134, 3.137, 5.510
 subordinator 4.103, 4.162, 4.166, 4.167, 4.170, 5.100, 5.167, 5.172, 5.187, 5.446, 5.447, 5.511–5.513, 5.516
 subordinators distributions 5.513
State dependent
 characteristic triplet 1.50, 1.52
 parameter 1.49, 1.50
State process upward 4.354
Stationarity 2.56, 2.60, 2.75, 2.225, 2.276, 2.277
Stationary
 ARMA processes 4.382
 distribution 2.55, 4.254, 4.256, 4.266, 4.267, 5.100
 field 1.78, 1.79
 Gaussian process 1.139, 1.140, 1.143, 1.145, 1.147, 2.267, 3.250, 5.72
 Gaussian series 1.185
 increment stochastic sequences 3.61
 independent increments 4.174
 probability 4.146, 4.153
 processes 2.321, 2.335
 sequences 3.60, 3.69
 sequences linear functionals 3.60
 version 1.38, 1.44, 1.45
Stiffness matrix 5.529
Stochastic
 boundedness 1.15, 1.18, 1.30
 differential equation (SDE) 3.2, 3.3, 3.15, 3.223, 3.270–3.273, 3.304, 5.85, 5.114, 5.319, 5.522
 distributions 3.250
 heat equation 1.129, 1.130
 integral 2.37, 2.219, 2.220
 measure (SM) 5.430
 representation formulae 2.402
 trend 2.52, 2.56, 2.57, 2.60, 2.63, 2.72, 2.77, 2.80, 2.81
 volatility 2.234, 2.235, 2.355, 2.356, 5.146
 volatility models 2.361, 2.366
Stochastically independent 5.39
Strike price 2.265, 2.362, 2.417
Strong asymptotic arbitrage (SAA) 5.416, 5.418
Subexponential distributions 3.81, 3.167, 4.67
Subfractional Brownian motion 4.15–4.17, 4.23
Subjective income 1.204
Submartingale 2.191
Subordinated
 Lévy process 4.168, 5.168, 5.180
 Poisson process 5.170, 5.176
Subordinator
 independent 4.164
 stable 4.103, 4.162, 4.166, 4.167, 4.170, 5.100, 5.167, 5.172, 5.187, 5.446, 5.447, 5.511–5.513, 5.516
Surplus process 1.169, 1.174, 1.175
Survival probability 4.135
Symmetric
 convex set 3.326, 3.327, 3.331, 3.333, 3.336, 3.338, 3.340–3.343, 3.357, 3.362
 distribution 2.134
 kernel 2.291
 Lévy measure 5.355, 5.360, 5.364, 5.367, 5.368, 5.378, 5.379
 Lévy process 5.298
 matrix 3.293, 3.299
 stable process 2.108, 5.451
Synergy index (SI) 4.110
T
Tail probability 5.141
Tapered data 1.181, 1.182
Target distribution 4.308
Tempered
 Hermite process 2.327, 2.328, 2.331, 2.332, 2.335
 stable processes 2.403
 stable subordinators (TSS) 5.446, 5.510, 5.513
 subordinators 5.446
Temporary insurance policy (TIP) 4.128
Term insurance policy (TIP) 4.132
Total least squares (TLS)
 estimator 3.48–3.50, 3.52, 3.288–3.290, 3.292, 3.301, 5.248, 5.252
 problem 3.48, 3.49, 3.288, 3.289
Transition
 density 2.108, 2.114, 2.125, 2.126
 matrix 4.146
 probability 4.247, 5.212
 probability density 1.34, 1.35, 1.38, 1.118, 1.119, 2.108–2.114, 2.118, 2.126, 2.166, 2.167, 2.252, 2.403, 2.412, 2.413, 3.224
 probability function 4.130, 4.131, 4.138
Translated process 3.344
Transportation distance 1.50–1.52, 1.59, 1.61, 1.62
Trimmed regions 1.152, 1.156, 1.157, 1.163
Truncated pseudomoments 2.96, 2.97
U
Ultimate ruin probability 2.422–2.426, 2.438, 5.130
Unbiased criterion 1.5, 1.10
Uncentered packing 2.374–2.377, 2.379
 dimension 2.373, 2.374, 2.379
Unconditional probability mass 4.145
Uncorrelated
 processes 2.240
 Wiener processes 2.234
Undiscounted process 2.238
Univariate
 distributions 4.287
 forecasts 2.61
 time series 2.52
Unobserved nonrandom vector 5.247
Unstable solution 3.192
V
VAR
 coefficients 2.61
 model 2.59–2.61, 2.68, 2.80, 2.82, 2.84, 2.88, 2.89
 model for exports 2.81
Vector
 autoregression 2.52, 2.59
 autoregressive process 5.58
Vitali coverings 3.120
Volatility
 function 2.235, 2.357
 process 2.234, 2.240, 2.356, 3.2, 4.354
 risk market price 2.240
 stochastic 2.234, 2.235, 2.355, 2.356
Volterra
 kernel 2.291, 2.293
 representation 2.291
W
Weak convergence 2.269, 2.327, 2.328, 2.334, 2.335, 2.345, 2.349, 3.2, 3.10, 3.12, 3.14, 3.192, 3.195, 3.204, 3.224
Weak large deviation principle (WLDP) 5.487
Weak solution 3.156, 3.197, 3.271, 3.272, 3.277, 3.306
Weekly separable family 1.8, 1.10
Weight function (WF) 4.234, 5.354, 5.355
Weighted differential entropy (WDE) 4.234
Weighted entropy power inequality (WEPI) 4.239
Weighted entropy power (WEP) 4.245
Weighted entropy (WE) 4.234
Weighted Fisher information inequality (WFII) 4.244
Weighted Fisher information matrix (WFIM) 4.237
Weighted information (WI) 4.247
Wiener process 1.52, 1.96, 1.104, 1.110, 1.154, 2.17, 2.19, 2.149–2.151, 2.203, 2.204, 2.215, 2.223, 2.235, 2.239, 2.240, 2.356, 2.357, 3.2, 3.3, 3.15, 3.98, 3.100, 3.146, 3.150, 3.182, 3.192, 3.196, 3.197, 3.199, 3.224, 3.225, 3.232, 3.233, 3.271–3.277, 3.281, 4.204, 4.210, 4.213, 4.216, 5.100, 5.204
Z
Zeta distribution 3.170, 3.171, 4.71
Zonotope 3.326–3.328, 3.331–3.333, 3.339, 3.347, 3.357, 3.360, 3.362
 approximation 3.326, 3.327, 3.362
 rotational 3.343
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MSTA

MSTA

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