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1. Bayesian Compendium. 1st ed. 2020
by Marcel van Oijen
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2020
オンライン: https://doi.org/10.1007/978-3-030-55897-0
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Preface
1 Introduction to Bayesian thinking
2 Introduction to Bayesian science
3 Assigning a prior distribution
4 Assigning a likelihood function
5 Deriving the posterior distribution
6 Sampling from any distribution by MCMC
7 Sampling from the posterior distribution by MCMC
8 Twelve ways to fit a straight line
9 MCMC and complex models
10 Bayesian calibration and MCMC: Frequently asked questions
11 After the calibration: Interpretation, reporting, visualization
2 Model ensembles: BMC and BMA
13 Discrepancy
14 Gaussian Processes and model emulation
15 Graphical Modelling (GM)
16 Bayesian Hierarchical Modelling (BHM)
17 Probabilistic risk analysis and Bayesian decision theory
18 Approximations to Bayes
19 Linear modelling: LM, GLM, GAM and mixed models
20 Machine learning
21 Time series and data assimilation
22 Spatial modelling and scaling error
23 Spatio-temporal modelling and adaptive sampling
24 What next?
Appendix 1: Notation and abbreviations
Appendix 2: Mathematics for modellers
Appendix 3: Probability theory for modellers
Appendix 4: R
Appendix 5: Bayesian software
Preface
1 Introduction to Bayesian thinking
2 Introduction to Bayesian science
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2. Statistical Modeling in Biomedical Research : Contemporary Topics and Voices in the Field. 1st ed. 2020
edited by Yichuan Zhao, Ding-Geng (Din) Chen
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2020
シリーズ名: Emerging Topics in Statistics and Biostatistics ;
オンライン: https://doi.org/10.1007/978-3-030-33416-1
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Preface
Part I: Next Generation Sequence Data Analysis
1. Modeling Species Specific Gene Expression Across Multiple Regions in the Brain
2. Classification of EEG Motion Artifact Signals Using Spatial ICA
3. Weighted K-means Clustering with Observation Weight for Single-cell Epigenomic Data
4. Discrete Multiple Testing in Detecting Differential Methylation Using Sequencing Data
Part II: Deep Learning, Precision Medicine and Applications
5. Prediction of Functional Markers of Mass Cytometry Data via Deep Learning
6. Building Health Application Recommender System Using Partially Penalized Regression
7. Hierarchical Continuous Time Hidden Markov Model, with Application in Zero-Inflated Accelerometer Data
Part III: Large Scale Data Analysis and its Applications
8. Privacy Preserving Feature Selection Via Voted Wrapper Method For Horizontally Distributed Medical Data
9. Improving Maize Trait through Modifying Combination of Genes
10. Molecular Basis of Food Classification in Traditional Chinese Medicine
11. Discovery Among Binary Biomarkers in Heterogeneous Populations
Part IV: Biomedical Research and the Modelling
12. Heat Kernel Smoothing on Manifolds and Its Application to Hyoid Bone Growth Modeling
13. Optimal Projections in the Distance-Based Statistical Methods
14. Kernel Tests for One, Two, and K-Sample Goodness-Of-Fit: State of the Art and Implementation Considerations
15. Hierarchical Modeling of the Effect of Pre-exposure Prophylaxis on HIV in the US
16. Mathematical Model of Mouse Ventricular Myocytes Overexpressing Adenylyl Cyclase Type 5
Part V: Survival Analysis with Complex Data Structure and its Applications
17. Non-Parametric Maximum Likelihood Estimator for Case-Cohort and Nested Case-Control Designs with Competing Risks Data
Authors: Jie-Huei Wang, Chun-Hao Pan, Yi-Hau Chen and I-Shou Chang
18. Variable Selection in Partially Linear Proportional Hazards Model with Grouped Covariates and a Diverging Number of Parameters
19. Inference of Transition Probabilities in Multi-state Models using Adaptive Inverse Probability Censoring Weighting Technique
Preface
Part I: Next Generation Sequence Data Analysis
1. Modeling Species Specific Gene Expression Across Multiple Regions in the Brain
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3. Chemometrics with R : Multivariate Data Analysis in the Natural and Life Sciences. 2nd ed. 2020
by Ron Wehrens
出版情報: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2020
シリーズ名: Use R! ;
オンライン: https://doi.org/10.1007/978-3-662-62027-4
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Introduction. - Data
Preprocessing
Principal Component Analysis
Self-Organizing Maps. - Clustering
Classification
Multivariate Regression. - Validation
Variable Selection
Chemometric Applications
Introduction. - Data
Preprocessing
Principal Component Analysis
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4. Mathematical Modeling and Computational Tools : ICACM 2018, Kharagpur, India, November 23–25. 1st ed. 2020
edited by Somnath Bhattacharyya, Jitendra Kumar, Koeli Ghoshal
出版情報: Singapore : Springer Singapore : Imprint: Springer, 2020
シリーズ名: Springer Proceedings in Mathematics & Statistics ; 320
オンライン: https://doi.org/10.1007/978-981-15-3615-1
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Part I: Electrokinetic Transport Phenomenon, P. P. Gopmandal, S. K. Maurya, S. Bhattacharyya, An overview on analytic expressions for electrophoretic mobility of rigid colloids
S. Bera, S. Bhattacharyya, Solute transport and mixing efficiency on electrokinetic flow in a heterogeneous microchannel
S. S. Barman and S. Bhattacharyya, Effect of temperature dependent electrostatic parameters on electroosmotic flow with hydrophobic patches
S. Jawalkar, O. Ojjela and D. Pradhan, Influence of thermophoresis and Brownian motion on MHD mixed convective chemically reacting couple stress fluid flow in porous medium between parallel plates
Part II Modelling of Fluid Flow, V. kumar, V. K. Srivastav and A. R. Paul, Computational fluid dynamics studies of effect of blockage ratio on drag
S. Mohan, S. Debnath, J. Kumar and K. Ghoshal, Distribution of two-dimensional unsteady sediment concentration in an open channel flow
P. Jain and K. Ghoshal, Solution to one dimensional diffusion equation with concentration dependent mixing length
A. Karthik, K. Sashank and T. S. L. Radhika, A study on the effect of various fluid, flow and mechanical parameters on the flow of Newtonian fluid in an expanding and contracting pipe
B. Kumar and G. S. Seth, Unsteady stagnation point nanofluid flow over a stretching sheet with thermal radiation
Y. D. Chashechkin, New universal classification of fluid flows structural components
T. K. Sengupta, S. Sengupta and P. Sundaram, Dynamical system theory of flow instability using the impulse and the frequency response approaches
L. Tlau and S. Ontela, Entropy generation for a mixed convection nanofluid flow in an inclined channel filled with porous medium with thermal radiation
Part III: Numerical Techniques to Physical Problems, S. Dutta and S. Bhattacharyya, Mixed convection in a lid-driven inclined cavity with discrete heater on the lower wall
P. Santra and G. S. Mahapatra, Discrete prey predator model with square root functional response under imprecise biological parameters
M. Adak, Comparison of explicit and implicit finite difference schemes on diffusion equation
H. Bansu and S. Kumar, Numerical solution of space and time fractional advection diffusion equation by meshless approach
A. Kumar, V. Kumar, M. umar, A. Kumar, V. K. Srivastav, R. Pandey and M. Kumar, Numerical studies of blockage in human heart
J. S. Chordiya and R. V. Sharma, Numerical analysis of partition-clustering in a high temperature gradient region for suppression of heat transfer in porous enclosure
N. Allwayin, D. G. Dilip, S. Panda and J. Mathew, Real time numerical scheme for crater geometry simulation in micro-EDM process
M. Mallick and S. Sundar, Existence, bifurcation and multiplicity results for a class of n x n p-Laplacian system
D. Ghosh and J. Kumar, Uniqueness and asymptotic behavior of the solutions to a singular coagulation-fragmentation equation
N. S. Bondareva and M. A. Sheremet, Natural convection melting of PCM: Numerical simulation techniques and applications
S. Koley, Hypersingular Integral Equation Approach for Hydroelastic Analysis of a Submerged Elastic Plate
J. Baroi and S. Anand Sahu, Dispersion of Bleustein- Gulyaev (BG) waves in smart composite structure
Part IV Graph Theory and Optimization: A. Doley and A. Bharali, The inverse sum indeg index for R-sum of graphs
D. Roy, Neural network based fuzzy multi objective optimisation for efficiency evaluation
D. K. Mohanty, R. K. Jana and M. P. Biswal, Multi-choice chance constrained programming Problems using genetic algorithm
A. Mahanta, A. Bharali and J. Buragohain, The ISI index of edge-semitotal and total graphs
J. Buragohain, A. Bharali and A. Mahanta, Four new operations of graphs related to tensor product and Zagerb indices
S. S. Negi, S. Abbas and M. Malik, Some oscillatory results for nonlinear equation on time scales
S. Gupta and L. N. Das, Optimal investment decision model based on simplex algorithm with variable optimal value evaluation process
Part V: Stochastic Modelling and Machine Learning (Computer), T. Maitra and S. Bhattacharya, Asymptotic theory of Bayes factor in stochastic differential equations with increasing number of individuals
D. Kavitha and V. Radha, Text detection based on text shape feature analysis with intelligent grouping in natural scene images
S. Seal, Anthrophilia* algorithm
S. Pasari, Stochastic modeling of earthquake interevent counts (natural times) in northwest Himalaya and adjoining regions
D. Baruah and A. Bharali, Analysis of three major airline networks of India: A complex network approach contents entries found
Part I: Electrokinetic Transport Phenomenon, P. P. Gopmandal, S. K. Maurya, S. Bhattacharyya, An overview on analytic expressions for electrophoretic mobility of rigid colloids
S. Bera, S. Bhattacharyya, Solute transport and mixing efficiency on electrokinetic flow in a heterogeneous microchannel
S. S. Barman and S. Bhattacharyya, Effect of temperature dependent electrostatic parameters on electroosmotic flow with hydrophobic patches
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5. Quantitative Methods in Pharmaceutical Research and Development : Concepts and Applications. 1st ed. 2020
edited by Olga V. Marchenko, Natallia V. Katenka
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2020
オンライン: https://doi.org/10.1007/978-3-030-48555-9
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Biostatistics in Clinical Trials
Pharmacometrics, A Quantitative Decision-Making Tool in Drug Development
Genomics and Bioinformatics in Biological Discovery and Pharmaceutical Development
Biostatistical Methods in Pharmacoepidemiology
Causal Inference in Pharmacoepidemiology
Statistical Data Mining of Clinical Data
Segmentation and Choice Models
Modern Analytic Techniques for Predictive Modeling of Clinical Trial Operations
Better Together: Examples of Biostatisticians Collaborating in Drug Development
Biostatistics in Clinical Trials
Pharmacometrics, A Quantitative Decision-Making Tool in Drug Development
Genomics and Bioinformatics in Biological Discovery and Pharmaceutical Development
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6. Design and Analysis of Subgroups with Biopharmaceutical Applications. 1st ed. 2020
edited by Naitee Ting, Joseph C. Cappelleri, Shuyen Ho, (Din) Ding-Geng Chen
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2020
シリーズ名: Emerging Topics in Statistics and Biostatistics ;
オンライン: https://doi.org/10.1007/978-3-030-40105-4
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1. Data-driven and Confirmatory Subgroup Analysis in Clinical Trials
2. Subgroup Analysis – A View from Industry
3. Biomarker-Targeted Confirmatory Trials
4. Considerations on Subgroup Analysis in Design and Analysis of Multi-Regional Clinical Trials
5. Practical Subgroup Identification Strategies in Late-stage Clinical Trials
6. Exploratory Subgroup Identification for Biopharmaceutical Development
7. Logical Inference on Treatment Efficacy When Subgroup Exists
8. The GUIDE Approach to Subgroup Identification and Inference
9. Use of the VG (Virtual Twins Combined with GUIDE) Method in the Development of Precision Medicines
10. Subgroups Identification for Tailored Therapies: a System of Methods, a Framework for Consistent Methodology Evaluation, and an Integrated Learn-and-confirm Approach
11. Developing and Validating Predictive Classifiers in Randomized Clinical Trials
12. Issues Related to Subgroup Analysis
13. Subgroup Analysis with Partial Linear Model
14. Subgroup Analysis in the 21st Century
15. Power of Statistical Tests for Subgroup Analysis in Meta-Analysis
16. Heterogeneity and Subgroup Analysis in Network Meta-Analysis
1. Data-driven and Confirmatory Subgroup Analysis in Clinical Trials
2. Subgroup Analysis – A View from Industry
3. Biomarker-Targeted Confirmatory Trials
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7. Statistical Methods and Applications in Forestry and Environmental Sciences. 1st ed. 2020
edited by Girish Chandra, Raman Nautiyal, Hukum Chandra
出版情報: Singapore : Springer Singapore : Imprint: Springer, 2020
シリーズ名: Forum for Interdisciplinary Mathematics ;
オンライン: https://doi.org/10.1007/978-981-15-1476-0
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Chapter 1. Measurement, Data and Statistics: A Historical Voyage in Indian Forestry
Chapter 2. National Forest Inventory in India: Developments Towards a New Design to Meet Emerging Challenges
Chapter 3. Internet of Things in Forestry and Environmental Sciences
Chapter 4. Inverse Adaptive Stratified Random Sampling
Chapter 5. Improved Nonparametric Estimation Using Partially Ordered Sets
Chapter 6. Bayesian Inference of a Finite Population Mean Under Length-Biased Sampling
Chapter 7. Calibration Approach Based Estimators for Finite Population Mean in Multistage Stratified Random Sampling
Chapter 8. A Joint Calibration Estimator of Population Total Under Entropy Distance Function Based on Dual Frame Surveys
Chapter 9. Fusing Classical Theories and Biomechanics Into Forest Modelling
Chapter 10. Statistical Multivariate Methods for Decision Making in Classification of Water Quality Data and Management of Water Resources
Chapter 11. Investigating Selection Criteria of Constrained Cluster Analysis: Applications in Forestry
Chapter 12. Ridge Regression Model for the Estimation of Total Carbon Sequestered by Forest Species
Chapter 13. Some Investigations on Designs for Mixture Experiments with Process Variable
Chapter 14. Development in Copula Applications in Forestry and Environmental Sciences
Chapter 15. Forest Cover Type Prediction Using Model Averaging
Chapter 16. Small Area Estimation for Skewed Semicontinuous Spatially Structured Responses
Chapter 17. Small Area Estimation for Total Basal Cover in the State of Maharashtra, India
Chapter 18. Estimation of Abundance of Asiatic Elephants in Elephant Reserves of Kerala State, India
Chapter 19. Exploration of Metagenomics Tools for Analysis of Forest Soil Microbial Diversity and its Annotation
Chapter 20. Integrated Survey Scheme to Capture Forestry Related Data in Bangladesh: Beyond the Traditional Approach
Chapter 1. Measurement, Data and Statistics: A Historical Voyage in Indian Forestry
Chapter 2. National Forest Inventory in India: Developments Towards a New Design to Meet Emerging Challenges
Chapter 3. Internet of Things in Forestry and Environmental Sciences
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8. Statistical Remedies for Medical Researchers. 1st ed. 2020
by Peter F. Thall
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2020
シリーズ名: Springer Series in Pharmaceutical Statistics ;
オンライン: https://doi.org/10.1007/978-3-030-43714-5
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1 Why Bother With Statistics?
2 Frequentists and Bayesians
3 Knocking Down the Straw Man
4 Science and Belief
5 The Perils of P-values
6 Flipping Coins
7 All Mixed Up
8 Sex, Biomarkers, and Paradoxes
9 Crippling New Treatments
10 Just Plain Wrong
11 Getting Personal
12 Multistage Treatment Regimes
References
1 Why Bother With Statistics?
2 Frequentists and Bayesians
3 Knocking Down the Straw Man
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9. Contemporary Experimental Design, Multivariate Analysis and Data Mining : Festschrift in Honour of Professor Kai-Tai Fang. 1st ed. 2020
edited by Jianqing Fan, Jianxin Pan
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2020
オンライン: https://doi.org/10.1007/978-3-030-46161-4
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Part I Review of Kai-Tai Fang’s Contribution
1 Walking on the Road to the Statistical Pyramid
2 The contribution to experimental designs by Kai-Tai Fang
3 From “Clothing Standard” to “Chemometrics”
4 A Review of Professor Kai-Tai Fang’s Contribution to the Education, Promotion, and Advancement of Statistics in China
Part II Design of Experiments
5 Is a Transformed Low Discrepancy Design Also Low Discrepancy?
6 The construction of optimal design for order-of-addition experiment via threshold accepting
7 Construction of Uniform Designs on Arbitrary Domains by Inverse Rosenblatt Transformation
8 Drug Combination Studies, Uniform Experimental Design and Extensions
9 Modified robust design criteria for Poisson mixed models
10 Study of Central Composite Design and Orthogonal Array Composite Design
11 Uniform design on manifold
Part III Multivariate Analysis
12 An Application of the Theory of Spherical Distributions in Multiple Mean Comparison
13 Estimating the Location Vector for Spherically Symmetric Distributions
14 On equidistant designs, symmetries and their violations in multivariate models
15 Estimation of covariance matrix with ARMA structure through quadratic loss function
Part IV Data Mining
16 Depth Importance in Precision Medicine (DIPM): A Tree and Forest Based Method
17 Bayesian Mixture Models with Weight-Dependent Component Priors
18 Cosine Similarity-Based Classifiers for Functional Data
Part V Hypothesis Test and Statistical Models
19 Projection Test with Sparse Optimal Direction for High-dimensional One Sample Mean Problem
20 Goodness-of-fit tests for correlated bilateral data from multiple groups
21 A Bilinear Reduced Rank Model
22 Simultaneous multiple change points estimation in generalized linear models
23 Data-Based Priors for Bayesian Model Averaging
24 Quantile regression with Gaussian kernels
Part I Review of Kai-Tai Fang’s Contribution
1 Walking on the Road to the Statistical Pyramid
2 The contribution to experimental designs by Kai-Tai Fang
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10. Recent Developments in Multivariate and Random Matrix Analysis : Festschrift in Honour of Dietrich von Rosen. 1st ed. 2020
edited by Thomas Holgersson, Martin Singull
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2020
オンライン: https://doi.org/10.1007/978-3-030-56773-6
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