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1. Advanced Statistics for Testing Assumed Causal Relationships : Multiple Regression Analysis Path Analysis Logistic Regression Analysis. 1st ed. 2020
by Hooshang Nayebi
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2020
シリーズ名: University of Tehran Science and Humanities Series ;
オンライン: https://doi.org/10.1007/978-3-030-54754-7
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目次情報:
1. Multiple Regression Analysis
2. Path Analysis
3. Logistic Regression Analysis
1. Multiple Regression Analysis
2. Path Analysis
3. Logistic Regression Analysis
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2. Analytical Methods in Statistics : AMISTAT, Liberec, Czech Republic, September 2019. 1st ed. 2020
edited by Matúš Maciak, Michal Pešta, Martin Schindler
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2020
シリーズ名: Springer Proceedings in Mathematics & Statistics ; 329
オンライン: https://doi.org/10.1007/978-3-030-48814-7
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Preface
Y. Güney, J. Jurečková and O. Arslan, Averaged Autoregression Quantiles in Autoregressive Model
J. Kalina and P. Vidnerová, Regression Neural Networks with a Highly Robust Loss Function
H. L. Koul and P. Geng, Weighted Empirical Minimum Distance Estimators in Berkson Measurement Error Regression Models
M. Maciak, M. Pešta and S. Vitali, Implied Volatility Surface Estimation via Quantile Regularization
I. Mizera, A remark on the Grenander estimator
U. Radojičić and K. Nordhausen, Non-Gaussian Component Analysis: Testing the Dimension of the Signal Subspace
P. Vidnerová, J. Kalina and Y. Güney, A Comparison of Robust Model Choice Criteria within a Metalearning Study
S. Zwanzig and R. Ahmad, On Parameter Estimation for High Dimensional Errors-in-Variables Models
Preface
Y. Güney, J. Jurečková and O. Arslan, Averaged Autoregression Quantiles in Autoregressive Model
J. Kalina and P. Vidnerová, Regression Neural Networks with a Highly Robust Loss Function
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3. Non-Asymptotic Analysis of Approximations for Multivariate Statistics. 1st ed. 2020
by Yasunori Fujikoshi, Vladimir V. Ulyanov
出版情報: Singapore : Springer Singapore : Imprint: Springer, 2020
シリーズ名: JSS Research Series in Statistics ;
オンライン: https://doi.org/10.1007/978-981-13-2616-5
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1. Introduction
2. Correlation Coefficient
3. MANOVA Test Statistics
4. Linear and Quadratic Discriminant Functions
5. Bootstrap Confidence Sets
6. Gaussian Comparison
7. Cornish-Fisher Expansions
8 Approximations for Statistics Based on Random Sample Sizes
9. Power-divergence Statistics
10.General Approach to Construct Non-asymptotic Bounds
11 - Other Topics
Index
1. Introduction
2. Correlation Coefficient
3. MANOVA Test Statistics
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4. Statistics for Data Science and Policy Analysis. 1st ed. 2020
edited by Azizur Rahman
出版情報: Singapore : Springer Singapore : Imprint: Springer, 2020
オンライン: https://doi.org/10.1007/978-981-15-1735-8
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Part I. Applied Statistics and Bayesian Modeling
1. Applied Bayesian Modeling for Assessment of Interpretation Uncertainty in Spatial Domain
2. Computing Robust Statistics via an EM Algorithm
3. Determining Risk Factors of Antenatal Care Attendance and its Frequency in Bangladesh: An Application of Count Regression Analysis
4. On Propensity Score Methodology
5. Asking Good Questions to Understand Voluntary Enrolments in Mathematics
PART II. Agricultural Statistics and Policy Analysis
6. Modeling for Prospect of Aman Rice Production in Dhaka Division, Bangladesh
7. Impacts and Determinants of Adoption in River-based Tilapia Cage Culture
8. Policy into Practice; Statistics the Forgotten Gatekeeper
9. Nutrient Loading in the River Systems around Major Cities in Bangladesh: a Quantitative Estimate with Consequences and Potential Recycling Options
10. Analysing Informal Milk Supply Chains Data to Identify Seasonal Occurrences of Antibiotic Residues
Part III. Data Science and Image Processing Statistics
11. Detection of Vegetation in Enviromental Repeat Photography: A New Algorithmic Approach in Data Science
12. Can Data Fusion increase the Performance of Action Detection in the Dark?
13. Data privacy and Security in the Cloud
14. Evaluating Faster-RCNN and YOLOv3 for Target Detection in Multi-sensor Data
15. Wavelet-based Quantile Density Function Estimation under Random Censorship
Part IV. Health Statistics and Social Policy
16. Factors Associated with Coronary Heart Disease among Elderly People in Different Communities
17. Finite Mixture Modelling Approach to Identify Factors Affecting Children ever Born for 15-49 Year Old Women in Asian Country
18. An Assessment of Influencing Factors for Motherhood During Childhood in Bangladesh Using Factor Analysis and Logistic Regression Methods
19. Effect of Women’s Education on Skilled Birth Attendants in South and South East Asia: A Cross-country assessment on Sustainable Development Goal 3.1
Part V. SMALL Area Estimation and Spatial Microsimulation
20. Estimation of Child Undernutrition at Disaggregated Administrative Tiers of a North-Eastern District of Bangladesh: An Application of Small Area Estimation Method
21. Using a Spatial Farm Microsimulation Model for Australia to Estimate the Impact of an External Shock on Farmer Incomes
Part VI. Business Analytics and Managements Policy Analysis
22. A tax benefit model for policy evaluation in Luxembourg: LuxTaxBen
23. Finding Significant Determinants and Impacts of Farm-Level Integrated Pest Management Practices Using Statistical Tools
24. Consumers Adoption Behavior Prediction through Technology Acceptance Model and Machine Learning Models
25. Shaping the Future of Multidimensional Project Management in Re-Tail Industry Using Statistical and Big-Data Theories
26. Technical Efficiency and Value Chain Analysis of Potato in a South-East Asian Country
27. Modelling and Analysis of Computer Experiments using a Simple Pendulum Model
Part I. Applied Statistics and Bayesian Modeling
1. Applied Bayesian Modeling for Assessment of Interpretation Uncertainty in Spatial Domain
2. Computing Robust Statistics via an EM Algorithm
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5. Pioneering Works on Distribution Theory : In Honor of Masaaki Sibuya. 1st ed. 2020
edited by Nobuaki Hoshino, Shuhei Mano, Takaaki Shimura
出版情報: Singapore : Springer Singapore : Imprint: Springer, 2020
シリーズ名: JSS Research Series in Statistics ;
オンライン: https://doi.org/10.1007/978-981-15-9663-6
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Gibbs Base Random Partitions
Asymptotic and approximate discrete distributions for length of Ewens sampling formula
An Error Bound for the Normal Approximation to the Length of a Ewens Partition
Distribution of Number of Levels in [s]-specified Random Permutation
Properties of General Systems of Orthogonal Polynomials with Symmetric Matrix Argument
Conjugate Analysis under Jeffreys' Prior with its Implications to Likelihood Inference
Gibbs Base Random Partitions
Asymptotic and approximate discrete distributions for length of Ewens sampling formula
An Error Bound for the Normal Approximation to the Length of a Ewens Partition
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6. An Introduction to Clustering with R. 1st ed. 2020
by Paolo Giordani, Maria Brigida Ferraro, Francesca Martella
出版情報: Singapore : Springer Singapore : Imprint: Springer, 2020
シリーズ名: Behaviormetrics: Quantitative Approaches to Human Behavior ; 1
オンライン: https://doi.org/10.1007/978-981-13-0553-5
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Section: Introduction
1.1 Introduction to clustering
1.2 R software
2. Section: Standard algorithms
2.1 Introduction
2.2 Distances and dissimilarities
2.3 Hierarchical methods
2.4 Non-hierarchical methods
2.5 Cluster validity
3. Section: Fuzzy algorithms
3.1 Introduction
3.2 Fuzzy K-means
3.3 Fuzzy K-medoids
3.4 Other fuzzy variants
3.5 Cluster validity
4. Section: Model-based algorithms
4.1 Introduction
4.2 Mixture of Gaussian distributions
4.3 Mixture of non-Gaussian distributions
4.4 Parsimonious mixture models
Section: Introduction
1.1 Introduction to clustering
1.2 R software
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7. Statistics Based on Dirichlet Processes and Related Topics. 1st ed. 2020
by Hajime Yamato
出版情報: Singapore : Springer Singapore : Imprint: Springer, 2020
シリーズ名: JSS Research Series in Statistics ;
オンライン: https://doi.org/10.1007/978-981-15-6975-3
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Introduction
Dirichlet process and Chinese restaurant process
Nonparametric estimation of estimable parameter
Random partition of positive integer
Introduction
Dirichlet process and Chinese restaurant process
Nonparametric estimation of estimable parameter
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8. Determining Sample Size and Power in Research Studies : A Manual for Researchers. 1st ed. 2020
by J. P. Verma, Priyam Verma
出版情報: Singapore : Springer Singapore : Imprint: Springer, 2020
オンライン: https://doi.org/10.1007/978-981-15-5204-5
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Chapter 1: Introduction To Sample Size Determination
Chapter 2: Understanding Statistical Inference
Chapter 3: Understanding Concepts In Estimating Sample Size In Survey Studies
Chapter 3: Chapter 4: Understanding Concepts In Estimating Sample Size In Hypothesis Testing Experiments Chapter 5: Use Of G*Power Software
Chapter 6: Determining Sample Size In Experimental Studies
Chapter 7: Determining Sample Size In General Linear Models
Chapter 1: Introduction To Sample Size Determination
Chapter 2: Understanding Statistical Inference
Chapter 3: Understanding Concepts In Estimating Sample Size In Survey Studies
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9. Advanced Studies in Classification and Data Science. 1st ed. 2020
edited by Tadashi Imaizumi, Akinori Okada, Sadaaki Miyamoto, Fumitake Sakaori, Yoshiro Yamamoto, Maurizio Vichi
出版情報: Singapore : Springer Singapore : Imprint: Springer, 2020
シリーズ名: Studies in Classification, Data Analysis, and Knowledge Organization ;
オンライン: https://doi.org/10.1007/978-981-15-3311-2
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Chapter 1. Multilevel model-based clustering: A new proposal of maximum-a-posteriori assignment
Chapter 2. Multi-citeria classifications in regional development modelling
Chapter 3. Non-parametric latent modeling and network clustering
Chapter 4. Efficient, Geometrically-adaptive Techniques for Multiscale Gaussian-kernel SVM Classification
Chapter 5. Random forests followed by computed ABC analysis as a feature selection method for machine-learning in biomedical data
Chapter 6. Non-Hierarchical Clustering for Large Data without Recalculating Cluster Center
Chapter 7. Supervised Nested Algorithm for Classification based on K-means
Chapter 8. Using Classification of Regions Based on the Complexity of the Global Progress Indices for Supporting Development in Competitiveness
Chapter 9. Estimation Methods Based on Weighting Clusters
Chapter 10. Five Strategies for Accommodating Overdispersion in Simple Correspondence Analysis
Chapter 11. From Joint Graphical Display to Bi-Modal Clustering: [2] Dual Space Versus Total Space
Chapter 12. Linear Time Visualization and Search in Big Data using Pixellated Factor Space Mapping
Chapter 13. From Joint Graphical Display to Bi-Modal Clustering: [1] A Giant Leap in Quantication Theory
Chapter 14. External Logistic Biplots for Mixed Types of Data
Chapter 15. Functional clustering approach for analysis of concentration
Chapter 16. Generalized additive models for the detection of copy number variations (CNVs) using multi gene panel sequencing data
Chapter 17. Variable selection for classification of multivariate functional data
Chapter 18. Initial value selection for the alternating least squares algorithm
Chapter 19. Inference for General MANOVA Based on ANOVA-Type Statistic
Chapter 20. How To Cross the River? - New ‘Distance’Measures
Chapter 21. New Statistical Matching Method Using Multinomial Logistic Regression Model
Chapter 22. Constructing graphical models for multi-source data: Sparse Network And Component analysis
Chapter 23. Understanding Malvestuto’s normalized mutual information
Chapter 24. Understanding the Rand index
Chapter 25. Layered Multivariate Regression with Its Applications
Chapter 26. An exploratory study on the clumpiness measure of intertransaction times: how is it useful for customer relationship management?
Chapter 27. Data Quality Management of Chain Stores based on Outlier Detection
Chapter 28. Analysis of expenditure pattens of virtual marriage households consisting of working couples synthesized by statistical matching method q
Chapter 29. The Effects of Natural Disasters on Household Income and Poverty in Rural Vietnam: An Analysis Using the Vietnam Household Living Standards Survey
Chapter 30. Generalizability of relationship between number of tweets about and sales of new beverage products
Chapter 31. Cluster Distance-Based Regression
Chapter 32. Bayesian network analysis of fashion behaviour
Chapter 33. Determining the Similarity Index in Electoral Behavior Analysis: An Issue Voting Behavioral:Mapping
Chapter 34. Well-Being Measures
Chapter 35. The Relationship between Household Assets and Choice to Work: Evidence from Japanese Official Microdata
Chapter 36. Visualization and Spatial Statistical Analysis for Vietnam Household Living Standard Survey
Chapter 37. Changes in the Gendered Division of Labor and Women’s Economic Contributions within Japanese Couples
Chapter 38. Employment structures vs. educational capital in the European Union regions
Chapter 39. The IPUMS Approach to Harmonizing the World’s Population Census Data
Chapter 40. A Supervised Multiclass Classifieras an Autocoding System for the Family Income and Expenditure Survey
Chapter 1. Multilevel model-based clustering: A new proposal of maximum-a-posteriori assignment
Chapter 2. Multi-citeria classifications in regional development modelling
Chapter 3. Non-parametric latent modeling and network clustering
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10. Pioneering Works on Extreme Value Theory : In Honor of Masaaki Sibuya. 1st ed. 2021
edited by Nobuaki Hoshino, Shuhei Mano, Takaaki Shimura
出版情報: Singapore : Springer Nature Singapore : Imprint: Springer, 2021
シリーズ名: JSS Research Series in Statistics ;
オンライン: https://doi.org/10.1007/978-981-16-0768-4
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Chap. 1 Estimation of generalized beta distributions (Authors: Sibuya and Mano)
Chap. 2 On Some Resampling Procedures with the Empirical Beta Copula (Kiriliouk, Segers and Tsukahara)
Chap. 3 Regression Analysis for Imbalanced Binary Data: Multi-Dimensional Case (Sei)
Chap. 4 An Analysis of Extremes: Semiparametric Efficiency in Regression (Ozeki and Doksum)
Chap. 5 Future Change in Relationships among Extreme Precipitation Statistics Using “d4PDF” (Tanaka)
Chap. 6 History and Perspectives of Hydrological Frequency Analysis in Japan (Takara)
Chap. 1 Estimation of generalized beta distributions (Authors: Sibuya and Mano)
Chap. 2 On Some Resampling Procedures with the Empirical Beta Copula (Kiriliouk, Segers and Tsukahara)
Chap. 3 Regression Analysis for Imbalanced Binary Data: Multi-Dimensional Case (Sei)