Sen / Sen Innovative Trend Methodologies in Science and Engineering

1. Auflage 2017
ISBN: 978-3-319-52338-5
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 360 Seiten, eBook

This book covers all types of literature on existing trend analysis approaches, but more than 60% of the methodologies are developed here and some of them are reflected to scientific literature and others are also innovative versions, modifications or improvements. The suggested methodologies help to design, develop, manage and deliver scientific applications and training to meet the needs of interested staff in companies, industries and universities including students.

Technical content and expertise are also provided from different theoretical and especially active roles in the design, development and delivery of science in particular and economics and business in general. It is also ensured that, wherever possible and technically appropriate, priority is given to the inclusion and integration of real life data, examples and processes within the book content.

The time seems right, because available books just focus on special sectors (fashion, social, business). This book reviews all the available trend approaches in the present literature on rational and logical bases.  

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Sen, Zekâi

Inhaltsverzeichnis

1;Preface;6
2;Contents;8
3;1 Introduction;13
3.1;Abstract;13
3.2;1.1 General;13
3.3;1.2 Trend Definition and Analysis;15
3.3.1;1.2.1 Conceptual and Visual Trends;16
3.3.2;1.2.2 Mathematical Trend;19
3.3.3;1.2.3 Statistical Trend;21
3.4;1.3 Trend in Some Disciplines;23
3.4.1;1.3.1 Atmospheric Sciences;24
3.4.2;1.3.2 Environmental Sciences;24
3.4.3;1.3.3 Earth Sciences;24
3.4.4;1.3.4 Engineering;25
3.4.5;1.3.5 Global Warming;25
3.4.6;1.3.6 Climate Change;26
3.4.7;1.3.7 Social Sciences;26
3.4.7.1;1.3.7.1 Economy;27
3.4.7.2;1.3.7.2 Business;27
3.4.7.3;1.3.7.3 Health;28
3.5;1.4 Pros and Cons of Trend Analysis;29
3.6;1.5 Future Research Directions;29
3.7;1.6 Purpose of This Book;30
3.8;References;31
4;2 Uncertainty and Time Series;33
4.1;Abstract;33
4.2;2.1 General;33
4.3;2.2 Random and Randomness;36
4.4;2.3 Empirical Frequency and Distribution Function;37
4.4.1;2.3.1 Empirical Frequency and Trend;40
4.5;2.4 Theoretical Probability Distribution Function (Pdf);42
4.6;2.5 Statistical Modeling;44
4.6.1;2.5.1 Deterministic-Uncertain Model;46
4.6.2;2.5.2 Probabilistic-Statistical Model;47
4.6.3;2.5.3 Transitional Probability Model;48
4.7;2.6 Stochastic Models;49
4.7.1;2.6.1 Homogeneity (Consistency);50
4.7.2;2.6.2 Stationarity;51
4.7.3;2.6.3 Periodicity (Seasonality);52
4.7.3.1;2.6.3.1 Known Period Case;55
4.8;2.7 Time Series Truncation;57
4.8.1;2.7.1 Statistical Truncations;59
4.9;2.8 Data Smoothing;61
4.9.1;2.8.1 Moving Averages;62
4.9.2;2.8.2 Difference Smoothing;62
4.10;2.9 Jump (Shift);64
4.11;2.10 Correlation Coefficients;65
4.11.1;2.10.1 Pearson Correlation Coefficient;66
4.11.2;2.10.2 Kendall Correlation Coefficient;70
4.11.3;2.10.3 Spearman Correlation Coefficient;71
4.12;2.11 Persistence/Nonrandomness;73
4.12.1;2.11.1 Short-Memory (Correlation) Components;73
4.12.2;2.11.2 Long-Memory (Persistence) Component;74
4.12.2.1;2.11.2.1 Rescaled Range and Hurst Phenomenon;75
4.13;References;77
5;3 Statistical Trend Tests;79
5.1;Abstract;79
5.2;3.1 General;79
5.3;3.2 Nonparametric Tests;80
5.3.1;3.2.1 Data Ordering (Ranks);81
5.4;3.3 Statistical Tests;82
5.4.1;3.3.1 Wald–Wolfowitz;82
5.4.2;3.3.2 Sign Test;82
5.4.3;3.3.3 Sign Difference Test;83
5.4.4;3.3.4 Run Test;84
5.4.5;3.3.5 Mann–Whitney (MW) Test;85
5.4.6;3.3.6 Kruskal–Wallis (KW) Test;91
5.4.7;3.3.7 Nonparametric Correlation Coefficient;95
5.4.8;3.3.8 Spearman’s Rho Test of Trend;96
5.4.9;3.3.9 Turning Point Test;97
5.4.10;3.3.10 Mann–Kendall (MK) Test;98
5.4.10.1;3.3.10.1 Mann–Kendall Trend Search;101
5.4.10.2;3.3.10.2 Sen Slope Estimator;102
5.4.10.3;3.3.10.3 Spearman’s Tau;103
5.4.10.4;3.3.10.4 Regression Trend;103
5.4.11;3.3.11 Two-Sample Wilcoxon Test;104
5.4.11.1;3.3.11.1 Signed-Wilcoxon Test;105
5.4.11.2;3.3.11.2 Wilcoxon Signed Rank Test;105
5.4.12;3.3.12 von Neuman Test;106
5.4.13;3.3.13 Cumulative Departures Test;107
5.4.13.1;3.3.13.1 Cumulative Deviations;107
5.4.14;3.3.14 Bayesian Test;109
5.4.15;3.3.15 Relative Error Test;110
5.4.16;3.3.16 t Test;111
5.4.17;3.3.17 Cramer Test;114
5.4.18;3.3.18 F Test;115
5.4.19;3.3.19 Truncation Test;118
5.4.20;3.3.20 Deviations Test;119
5.4.21;3.3.21 Subtraction Test;119
5.4.22;3.3.22 ?en Autorun Test;120
5.4.23;3.3.23 Seasonal Kendall Test;123
5.5;3.4 Unit Root Model Trend Determination;124
5.5.1;3.4.1 Integration and Dickey–Fuller (DF) Test;125
5.5.2;3.4.2 The Kwiatkowski, Phillips, Schmidt, and Shin Test;126
5.5.3;3.4.3 Critical Values of the KPSS Test;129
5.5.4;3.4.4 Empirical Power of the KPSS;130
5.5.5;3.4.5 Example: Comparison of the DF and KPSS Tests for Several Macro-Economic Time Series;133
5.5.5.1;3.4.5.1 Test of Stationarity Around Mean;133
5.5.5.2;3.4.5.2 Test of Stationarity Around a Linear Trend;136
5.6;3.5 Parametric Tests;136
5.6.1;3.5.1 Regression Analysis;138
5.6.2;3.5.2 Regression Line Assumptions;139
5.6.3;3.5.3 Goodness of Fit (R2) for Regression;140
5.6.4;3.5.4 Cumulative Sum (CUSUM) Method;141
5.7;References;142
6;4 Temporal Trend Analysis;145
6.1;Abstract;145
6.2;4.1 General;145
6.3;4.2 Visual Inspection;147
6.4;4.3 Monotonic Trend Analysis;149
6.5;4.4 Scatter Diagrams and Regression Model;150
6.6;4.5 Linear Regression Model;153
6.6.1;4.5.1 Statistical Procedure;154
6.7;4.6 Unrestricted Regression Model;157
6.7.1;4.6.1 Application;159
6.8;4.7 Partial Regression Method (PRM);160
6.9;4.8 Cluster Regression and Markov Chain;163
6.9.1;4.8.1 Cluster Regression Model;164
6.9.2;4.8.2 Application and Discussion;165
6.10;4.9 Trend Over-whitening Procedures;171
6.10.1;4.9.1 Over-whitening (OW) Process;172
6.10.2;4.9.2 Simulation;176
6.10.3;4.9.3 Application;177
6.11;References;185
7;5 Innovative Trend Analyses;187
7.1;Abstract;187
7.2;5.1 General;187
7.3;5.2 Probability Distribution-Statistical Parameter Trend Implications;189
7.4;5.3 Innovative Trend Identification Methodologies;194
7.4.1;5.3.1 Application;196
7.5;5.4 Innovative Trend Simulation;198
7.5.1;5.4.1 Fundamental Methodology;200
7.5.1.1;5.4.1.1 Simulation Methodology;201
7.5.1.2;5.4.1.2 Dependent Process Simulation Results;204
7.6;5.5 Innovative Trend Significance Test;211
7.6.1;5.5.1 Deterministic Basis;212
7.6.2;5.5.2 Stochastic Basis;214
7.6.2.1;5.5.2.1 Normally Distributed Stochastic Time Series;214
7.6.2.2;5.5.2.2 Gamma Distributed Stochastic Time Series;215
7.6.3;5.5.3 Statistical Innovative Trend Test;216
7.6.4;5.5.4 Application;217
7.7;5.6 Crossing Trend Analysis Methodology;222
7.7.1;5.6.1 Rational Concept;224
7.7.2;5.6.2 Theoretical Background;224
7.7.3;5.6.3 Monte Carlo Simulations;227
7.7.4;5.6.4 Application;227
7.8;References;237
8;6 Spatial Trend Analysis;239
8.1;Abstract;239
8.2;6.1 General;239
8.3;6.2 Numerical Solution;242
8.4;6.3 Spatial Data Analysis;244
8.5;6.4 Homogeneity and Isotropy;247
8.6;6.5 Spatial Trend Surfaces;250
8.6.1;6.5.1 Horizontal Plane;252
8.6.2;6.5.2 Horizontal Planes;253
8.6.3;6.5.3 Inclined Trend Plane;253
8.6.4;6.5.4 Inclined Trend Planes;254
8.6.5;6.5.5 Curved Trend Surface;255
8.6.6;6.5.6 Random Surface;255
8.7;6.6 Spatial Dependence Function (SDF);257
8.7.1;6.6.1 Spatial Correlation Parameter Calculation;259
8.8;6.7 Double Mass Curve Test;262
8.9;6.8 Trend Surface Analysis;266
8.9.1;6.8.1 Planer Trend Regression Analysis;266
8.9.2;6.8.2 Polynomial Trend Regression Analysis;269
8.9.3;6.8.3 Kriging Methodology;274
8.9.3.1;6.8.3.1 Simple Kriging (SK);277
8.9.3.1.1;Methodology;277
8.10;6.9 Triple Diagram Model (TDM);283
8.10.1;6.9.1 Parallel-Triple Model;284
8.10.2;6.9.2 Serial-Triple Model;288
8.11;References;292
9;7 Trend Variability Detection;293
9.1;Abstract;293
9.2;7.1 General;293
9.3;7.2 Variability Measures;295
9.3.1;7.2.1 Range;295
9.3.2;7.2.2 Standard Deviation;296
9.3.3;7.2.3 The Interquartile Range (IQR);298
9.3.4;7.2.4 Investment Variability;299
9.4;7.3 Trend and Variability Detection by Innovative Methodology;300
9.4.1;7.3.1 Methodology;301
9.4.2;7.3.2 Simulation Study;304
9.4.3;7.3.3 Applications;306
9.5;7.4 Trend Significance Limits;309
9.6;7.5 Trend and Variability Analyses by Innovative and Classical Methodologies;316
9.6.1;7.5.1 ?en Innovative Trend Analysis;317
9.7;7.6 Application and Interpretations;318
9.7.1;7.6.1 Probability Distribution Functions (pdf);320
9.7.2;7.6.2 Different Trends;321
9.8;7.7 Trend and Variability;323
9.9;7.8 Innovative Trend Template and Significance Limits;326
9.10;References;329
10;8 Partial Trend Detection;332
10.1;Abstract;332
10.2;8.1 General;332
10.3;8.2 Qualitative Partial Trend Methodology;335
10.4;8.3 Previous Works;337
10.5;8.4 Innovative Piecewise Trend Analysis;341
10.6;8.5 Innovative Trend Template;346
10.7;8.6 Stochastic Simulation Approach;348
10.8;8.7 Data and the Study Area;352
10.8.1;8.7.1 Partial Trend Groups;352
10.8.2;8.7.2 Partial Trend Lines;353
10.9;References;356
11;Index;358

Über Autor(innen)

Prof. Zekâi Sen obtained his B.Sc. and M.Sc. degrees from Technical University of Istanbul, Civil Engineering Faculty, Department of Reinforced Concrete in 1971. His further post-graduate studies were carried out at the University of London, Imperial College of Science and Technology. He was granted Diploma of Imperial College (D.I.C) and M.Sc. in Engineering Hydrology in 1972 and Ph. D. in stochastic hydrology in 1974. He worked in different countries such as England, Norway, Saudi Arabia and Turkey. He worked in different faculties as the head of department. His main interests are hydrology, water resources, hydrogeology, hydrometeorology, hydraulics, science philosophy and history. He has published numerous (Science Citation Indexed) SCI scientific papers in different internationally top journals on various topics in addition to numerous publications in international conferences, symposiums and technical reports as well as edited proceedings and books. Under his supervision many students from different countries (Turkey, Saudi Arabia, Yemen, Jordan, Libya, and Pakistan) have obtained Ph. D. degrees in different energy aspects and water science topics. He holds several national and international scientific prizes and the most recent one is given as a team work due to his contribution to "Nobel Peace Prize" through his works in IPCC form 2002-2007 concerning Climate Change. He is currently working at the Technical University of Istanbul, Civil Engineering Faculty. He is also the president of Turkish Water Foundation.