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2022年5月2日　159タイトル追加
2021年12月24日　19タイトル追加

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A　 B　 C　 D　 E　 F　 G　 H　 I　 J　K　 L　 M　 N　 O　 P　 Q　 R　 S　 T　 U　 V　 W　X　Y　Z






A






  1. A primer on experiments with mixtures
  2. A user's guide to principal components
  3. Advanced analysis of variance
  4. Advanced experimental design (Design and Analysis of Experiments 2)
  5. An elementary introduction to statistical learning theory
  6. An introduction to envelopes :dimension reduction for efficient estimation in multivariate statistics
  7. An introduction to probability and statistics
  8. Analysis of ordinal categorical data
  9. Applied Bayesian modeling and causal inference from incomplete-data perspectives :an essential journey with Donald Rubin's statistical family
  10. Applied Bayesian modelling
  11. Applied logistic regression
  12. Applied longitudinal analysis
  13. Applied MANOVA and discriminant analysis
  14. Applied multiway data analysis
  15. Applied regression analysis
  16. Applied survival analysis :regression modeling of time-to-event data
  17. Approximate dynamic programmingsolving the curses of dimensionality






B






  1. Basic and advanced Bayesian structural equation modeling : with applications in the medical and behavioral sciences
  2. Batch effects and noise in microarray experiments :sources and solutions
  3. Bayes linear statistics :theory and methods
  4. Bayesian analysis for the social sciences
  5. Bayesian analysis of stochastic process models
  6. Bayesian models for categorical data
  7. Bayesian networks :an introduction
  8. Bayesian statistical modelling
  9. Bayesian statistics and marketing
  10. Bias and causation :models and judgment for valid comparisons
  11. Biostatistical methods :the assessment of relative risks
  12. Biostatistics :a methodology for the health sciences
  13. Bootstrap methods :a guide for practitioners and researchers






C






  1. Case Studies in Bayesian Statistical Modelling and Analysis
  2. Causality :statistical perspectives and applications
  3. Clinical trials :a methodologic perspective
  4. Cluster Analysis
  5. Combinatorial methods in discrete distributions
  6. Constrained statistical inference :inequality, order, and shape restrictions
  7. Contemporary Bayesian econometrics and statistics
  8. Correspondence analysis :theory, practice and new strategies






D






  1. Data analysis :what can be learned from the past 50 years
  2. Decision theory :principles and approaches
  3. Design and analysis of clinical trialsconcepts and methodologies
  4. Dirichlet and Related Distributions :Theory, Methods and Applications






E






  1. Empirical model building :data, models, and reality
  2. Environmental statistics :methods and applications
  3. Exploration and analysis of DNA microarray and other high-dimensional data
  4. Extremes in random fields :a theory and its applications






F






  1. Fast sequential Monte Carlo methods for counting and optimization
  2. Finding groups in data :an introduction to cluster analysis
  3. Flowgraph models for multistate time-to-event data
  4. Fractal-based point processes
  5. Fundamental statistical inference :a computational approach
  6. Fundamentals of queueing theory






G






  1. Game-theoretic foundations for probability and finance
  2. Generalized linear models : with applications in engineering and the sciences
  3. Geometry driven statistics
  4. Geostatistics :modeling spatial uncertainty






H






  1. Handbook of monte carlo methods
  2. High-dimensional covariance estimation






I






  1. Image processing and jump regression analysis
  2. Inference and prediction in large dimensions
  3. Information and exponential families in statistical theory
  4. Introduction to experimental design (Design and Analysis of Experiments 1)
  5. Introduction to imprecise probabilities
  6. Introduction to nonparametric regression
  7. Introductory stochastic analysis for finance and insurance






L






  1. Latent class and latent transition analysis :with applications in the social behavioral, and health sciences
  2. Latent curve models :a structural equation perspective
  3. Latent variable models and factor analysis : a unified approach
  4. Linear models :the theory and application of analysis of variance
  5. Linear regression analysis
  6. Long-memory time series :theory and methods
  7. Longitudinal data analysis
  8. Lower previsions






M






  1. Management of data in clinical trials
  2. Markov chains :analytic and Monte Carlo computations
  3. Markov decision processes :discrete stochastic dynamic programming
  4. Markov processes and applications :algorithms, networks, genome and finance
  5. Matrix differential calculus with applications in statistics and econometrics
  6. Measuring agreement :models, methods, and applications
  7. Meta analysis :a guide to calibrating and combining statistical evidence
  8. Methodological developments in data linkage
  9. Methods of multivariate analysis
  10. Mixtures :estimation and applications
  11. Modelling under risk and uncertainty :an introduction to statistical, phenomenological, and computational methods
  12. Models for probability and statistical inference :theory and applications
  13. Modern applied U-statistics
  14. Modern experimental design
  15. Modern regression methods
  16. Modes of parametric statistical inference
  17. Multilevel statistical models
  18. Multiple imputation for nonresponse in surveys
  19. Multistate systems reliability :theory with applications
  20. Multivariable model-building :a pragmatic approach to regression analysis based on fractional polynomials for modelling continuous variables
  21. Multivariate density estimation :theory, practice, and visualization
  22. Multivariate statistics :high-dimensional and large-sample approximations






N






  1. Nonlinear regression
  2. Nonparametric analysis of univariate heavy-tailed data research and practice
  3. Nonparametric finance
  4. Nonparametric hypothesis testing : rank and permutation methods with applications in R
  5. Nonparametric regression methods for longitudinal data analysis
  6. Nonparametric statistical methods
  7. Nonparametric statistics with applications to science and engineering
  8. Numerical issues in statistical computing for the social scientist






O






  1. Operational risk :modeling analytics
  2. Optimal learning






P






  1. Periodically correlated random sequences :spectral theory and practice
  2. Permutation tests for complex data :theory, applications, and software
  3. Planning, construction, and statistical analysis of comparative experiments
  4. Precedence-type tests and applications
  5. Preparing for the worst :incorporating downside risk in stock market investments
  6. Probability and conditional expectation :fundamentals for the empirical sciences






      7. Q






      1. Quantile regression :estimation and simulation
      2. Quantile regression :theory and applications






      R






      1. Random data :analysis and measurement procedures
      2. Randomization in clinical trials :theory and practice
      3. Recent advances in quantitative methods for cancer and human health risk assessment
      4. Regression Analysis by Example
      5. Regression with social data :modeling continuous and limited response variables
      6. Reinsurance : actuarial and statistical aspects
      7. Reliability and risk :a Bayesian perspective
      8. Response surfaces, mixtures, and ridge analyses
      9. Robust correlation : theory and applications
      10. Robust methods in biostatistics
      11. Robust regression and outlier detection
      12. Robust statistics
      13. Robust statistics : theory and methods (with R)
      14. Robustness theory and application






      S






      1. Sample Size Determination and Power
      2. Simulation and Monte Carlo :with applications in finance and MCMC
      3. Smoothing of multivariate data :density estimation and visualization
      4. Solutions manual to accompany, simulation and the Monte Carlo method
      5. Spatial and spatio-temporal geostatistical modeling and kriging
      6. Spatial statistics and spatio-temporal data :covariance functions and directional properties
      7. Special designs and applications (Design and Analysis of Experiments 3)
      8. Stage-wise adaptive designs
      9. Statistical advances in the biomedical sciences : clinical trials, epidemiology, survival analysis, and bioinformatics
      10. Statistical analysis of profile monitoring
      11. Statistical control by monitoring and adjustment
      12. Statistical inference for fractional diffusion processes
      13. Statistical intervals : a guide for practitioners and researchers
      14. Statistical meta-analysis with applications
      15. Statistical methods for fuzzy data
      16. Statistical methods for quality improvement
      17. Statistical methods for rates and proportions
      18. Statistical methods in diagnostic medicine
      19. Statistical methods in spatial epidemiology
      20. Statistical rules of thumb
      21. Statistical shape analysis with applications in R
      22. Statistical tolerance regions :theory, applications, and computation
      23. Statistics and causality :methods for applied empirical research
      24. Statistics for research
      25. Statistics for spatial data
      26. Statistics of extremes : theory and applications
      27. Stochastic geometry and its applications
      28. Structural equation modeling :a Bayesian approach
      29. Structural equation modeling :applications using Mplus
      30. Structural equations with latent variables
      31. Survey measurement and process quality






      T






      1. The analysis of covariance and alternatives :statistical methods for experiments, quasi-experiments, and single-case studies
      2. The construction of optimal stated choice experiments :theory and methods
      3. The EM algorithm and extensions
      4. The fitness of information :quantitative assessments of critical evidence
      5. The statistical analysis of failure time data
      6. The theory of response-adaptive randomization in clinical trials
      7. Theoretical foundations of functional data analysis, with an introduction to linear operators
      8. Theory of preliminary test and Stein-type estimation with applications
      9. Theory of probability :a critical introductory treatment
      10. Theory of ridge regression estimation with applications
      11. Time series analysis :forecasting and control
      12. Time series analysis :nonstationary and noninvertible distribution theory
      13. Time Series Analysis and Forecasting By Example
      14. Time series analysis with long memory in view






      U






      1. Uncertainty analysis with high dimensional dependence modelling
      2. Understanding uncertainty
      3. Univariate discrete distributions
      4. Using the Weibull distribution :reliability, modeling, and inference






      V




      1. Variations on split plot and split block experiment designs
      2. Visual statistics :seeing data with dynamic interactive graphics


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