314
Index
PyHasse (software package), 156
application
data matrix, 295–296
artificial intelligence, 293
conventional, 299, 300
data matrix, 292
development, 294
dominance analysis, 114
Duquenne/Guigues basis, 86–87
graphical user interface, 74
HDs, 110
hdsimpl, 300–302
Internet and the web-based notebook, xvi
lattice theoretical method in BK, 91
linear extensions, 293
notebook, 305, 306
online version
first impression, 296
modules, 298
tags and categories, 297
partially ordered sets, 293
partial order, 116
pillars, 304
set of indicator values, 292
Spyout, 298–299
Pyrolysis features, 165
Python, 294
R
Rand index, 31, 35
Ranked set sampling (RSS)
auxiliary variable, 138
d X m units, 139, 140
efficient sampling strategy, 138
JPS, 137–138
LTR, 139
measurement and units, 139
multivariate variables, 141
research, 137
sample unit, 137
VSR, 139
Refrigerants, 83, 84, 86, 92, 98–99
Resilience, 20
Retro-regression analysis, 270–271
Reverse clustering
capacities and effectiveness, 33
categorization, 35
choice of variables, 40
classification, potential situations, 36, 37
Rand index, 31, 35
“supervised classifier choice”, 35
working of entire procedure, 32
Risk assessment, 159
S
Safety assessment, 159
Sampling theory
auxiliary variables, 136, 137
calculations, 148–149
development, 135
efficient strategies, 136
estimation stage, 135
Hasse diagram, 144–147
LEs, 144–147
methods, 148–149
multivariate ranked set sampling, 141
multivariate variables, 136
MVSR, 142–144
negative correlation, 147–148
poset, 144–147
randomization, 135–136
representation, 135, 136
sampling stage, 135
sorting, 141, 142
Scaling procedure, 24, 91
Scoring methods, 267
Sensitivity analysis, 156, 171
Simple average ranking (SAR), 282
Simple random sample (SRS), 136
Simple systems, 18, 20
Simulation, 4, 10–12, 124, 125
Singular Value Decomposition, 225, 235
Social sciences
average height, 226, 228
basic definitions, 221
cluster analysis, 239
conflicting scores, 219
data structure and tools, 220
dominance eigenvector, 226, 228
economic indicators, 225, 226
frequency and cumulative distributions, 231
graphical representation, 222
Hasse diagram, 225, 227
integration, 239
linear extension, 222
linear/logistic regression, 239
matrix representations, 222
MRP, 223
multi-criteria decision problems, 220
multidimensional benchmarks, 228–230
numerical data systems, 219
ordinal attributes, 230
partial order theory, 221, 239
populations, 232–235
posetic algorithms, 239
precise formulation, 239
social traits, 219
socioeconomic field, 220–221
Index
PyHasse (software package), 156
application
data matrix, 295–296
artificial intelligence, 293
conventional, 299, 300
data matrix, 292
development, 294
dominance analysis, 114
Duquenne/Guigues basis, 86–87
graphical user interface, 74
HDs, 110
hdsimpl, 300–302
Internet and the web-based notebook, xvi
lattice theoretical method in BK, 91
linear extensions, 293
notebook, 305, 306
online version
first impression, 296
modules, 298
tags and categories, 297
partially ordered sets, 293
partial order, 116
pillars, 304
set of indicator values, 292
Spyout, 298–299
Pyrolysis features, 165
Python, 294
R
Rand index, 31, 35
Ranked set sampling (RSS)
auxiliary variable, 138
d X m units, 139, 140
efficient sampling strategy, 138
JPS, 137–138
LTR, 139
measurement and units, 139
multivariate variables, 141
research, 137
sample unit, 137
VSR, 139
Refrigerants, 83, 84, 86, 92, 98–99
Resilience, 20
Retro-regression analysis, 270–271
Reverse clustering
capacities and effectiveness, 33
categorization, 35
choice of variables, 40
classification, potential situations, 36, 37
Rand index, 31, 35
“supervised classifier choice”, 35
working of entire procedure, 32
Risk assessment, 159
S
Safety assessment, 159
Sampling theory
auxiliary variables, 136, 137
calculations, 148–149
development, 135
efficient strategies, 136
estimation stage, 135
Hasse diagram, 144–147
LEs, 144–147
methods, 148–149
multivariate ranked set sampling, 141
multivariate variables, 136
MVSR, 142–144
negative correlation, 147–148
poset, 144–147
randomization, 135–136
representation, 135, 136
sampling stage, 135
sorting, 141, 142
Scaling procedure, 24, 91
Scoring methods, 267
Sensitivity analysis, 156, 171
Simple average ranking (SAR), 282
Simple random sample (SRS), 136
Simple systems, 18, 20
Simulation, 4, 10–12, 124, 125
Singular Value Decomposition, 225, 235
Social sciences
average height, 226, 228
basic definitions, 221
cluster analysis, 239
conflicting scores, 219
data structure and tools, 220
dominance eigenvector, 226, 228
economic indicators, 225, 226
frequency and cumulative distributions, 231
graphical representation, 222
Hasse diagram, 225, 227
integration, 239
linear extension, 222
linear/logistic regression, 239
matrix representations, 222
MRP, 223
multi-criteria decision problems, 220
multidimensional benchmarks, 228–230
numerical data systems, 219
ordinal attributes, 230
partial order theory, 221, 239
populations, 232–235
posetic algorithms, 239
precise formulation, 239
social traits, 219
socioeconomic field, 220–221