#
Wiley series in probability and statistics
Resource Information
The series ** Wiley series in probability and statistics** represents a set of related resources, especially of a specified kind, found in **University of Oklahoma Libraries**.

The Resource
Wiley series in probability and statistics
Resource Information

The series

**Wiley series in probability and statistics**represents a set of related resources, especially of a specified kind, found in**University of Oklahoma Libraries**.- Label
- Wiley series in probability and statistics

## Context

Context of Wiley series in probability and statistics#### Members

- Wiley series in probability and statistics, 706
- Wiley series in probability and statistics, 755
- Wiley series in probability and statistics, 794
- Wiley series in probability and statistics, Applied probability and statistics
- Wiley series in probability and statistics, Biostatistics section
- Wiley series in probability and statistics, Financial engineering section
- Wiley series in probability and statistics, Probability and statistics
- Wiley series in probability and statistics, Survey methodology section
- Wiley series in probability and statistics, Texts, references, and pocketbooks section
- A primer on experiments with mixtures
- A primer on experiments with mixtures
- Advanced analysis of variance
- An elementary introduction to statistical learning theory
- An elementary introduction to statistical learning theory
- An introduction to probability and statistics
- Analysis of ordinal categorical data
- Applied Bayesian modelling
- Applied Bayesian modelling
- Applied MANOVA and discriminant analysis
- Applied linear regression
- Applied logistic regression
- Applied logistic regression
- Applied longitudinal analysis
- Applied spatial statistics for public health data
- Approximate dynamic programming : solving the curses of dimensionality
- Basic and advanced Bayesian structural equation modeling : with applications in the medical and behavioral sciences
- Basic and advanced structural equation modeling : with applications in the medical and behavioral sciences
- Batch effects and noise in microarray experiments : sources and solutions
- Bayesian analysis for the social sciences
- Bayesian analysis of stochastic process models
- Bayesian analysis of stochastic process models
- Bayesian models for categorical data
- Bayesian statistical modelling
- Bias and causation : models and judgment for valid comparisons
- Biostatistical methods : the assessment of relative risks
- Biostatistics : a methodology for the health sciences
- Case studies in reliability and maintenance
- Categorical data analysis
- Causality : statistical perspectives and applications
- Causality : statistical perspectives and applications
- Clinical trials : a methodologic perspective
- Cluster analysis
- Computational statistics
- Correspondence analysis : theory, practice and new strategies
- Data analysis : what can be learned from the past 50 years
- Decision theory : principles and approaches
- Design and analysis of experiments, Volume 3, Special designs and applications
- Design and analysis of experiments, Volume 3, Special designs and applications
- Dirichlet and related distributions : theory, methods and applications
- Empirical model building : data, models, and reality
- Engineering biostatistics : an introduction using MATLAB and WinBUGS
- Experiments : planning, analysis, and optimization
- Exploration and analysis of DNA microarray and other high-dimensional data
- Exploratory data mining and data cleaning
- Extremes in random fields : a theory and its applications
- Fast sequential Monte Carlo methods for counting and optimization
- Foundations of linear and generalized linear models
- Generalized linear models : with applications in engineering and the sciences
- Geometry driven statistics
- Geostatistics : modeling spatial uncertainty
- High-dimensional covariance estimation
- Implementation of large-scale education assessments
- Introduction to imprecise probabilities
- Introduction to linear regression analysis
- Introduction to nonparametric regression
- Introduction to time series analysis and forecasting
- Introductory biostatistics for the health sciences : modern applications including bootstrap
- Introductory biostatistics for the health sciences : modern applications including bootstrap
- Introductory stochastic analysis for finance and insurance
- Latent class and latent transition analysis : with applications in the social behavioral, and health sciences
- Latent curve models : a structural equation perspective
- Latent variable models and factor analysis : a unified approach
- Latent variable models and factor analysis : a unified approach
- Linear statistical models
- Longitudinal data analysis
- Lower previsions
- Machine learning : a concise introduction
- Markov chains : analytic and Monte Carlo computations
- Markov chains : analytic and Monte Carlo computations
- Matrix analysis for statistics
- Measuring agreement : models, methods, and applications
- Methodological developments in data linkage
- Methods and applications of linear models : regression and the analysis of variance
- Methods of multivariate analysis
- Mixed models : theory and applications with R
- Mixtures / : estimation and applications
- Modern experimental design
- Multivariate density estimation : theory, practice, and visualization
- Multivariate statistics : high-dimensional and large-sample approximations
- Multivariate time series analysis : with R and financial applications
- Nonparametric analysis of univariate heavy-tailed data : research and practice
- Nonparametric hypothesis testing : rank and permutation methods with applications in R
- Nonparametric regression methods for longitudinal data analysis : [mixed-effects modeling approaches]
- Nonparametric statistical methods
- Operational risk : modeling analytics
- Optimal learning
- Practical strategies for experimenting
- Quantile regression : theory and applications
- Random data : analysis and measurement procedures
- Random graphs for statistical pattern recognition
- Regression analysis by example
- Regression diagnostics : identifying influential data and sources of collinearity
- Regression models for time series analysis
- Regression with social data : modeling continuous and limited response variables
- Response surface methodology : process and product optimization using designed experiments
- Response surface methodology : process and product optimization using designed experiments
- Robust Statistics : Theory and Methods
- Robust correlation : theory and applications
- Robust statistics
- Simulation and the monte carlo method
- Smoothing of multivariate data : density estimation and visualization
- Spatial and spatio-temporal geostatistical modeling and kriging
- Spatial statistics and spatio-temporal data : covariance functions and directional properties
- Statistical analysis of designed experiments : theory and applications
- Statistical analysis of profile monitoring
- Statistical analysis of profile monitoring
- Statistical control by monitoring and adjustment
- Statistical distributions
- Statistical inference for fractional diffusion processes
- Statistical intervals : a guide for practitioners and researchers
- Statistical methods for quality improvement
- Statistical methods for rates and proportions
- Statistical methods for survival data analysis
- Statistical shape analysis with applications in R
- Statistical tolerance regions : theory, applications, and computation
- Statistics and causality : methods for applied empirical research
- Statistics for research
- Statistics for spatio-temporal data
- Statistics of extremes : theory and applications
- Stochastic geometry and its applications
- Structural equation modeling : applications using Mplus
- The analysis of covariance and alternatives : statistical methods for experiments, quasi-experiments, and single-case studies
- The statistical analysis of failure time data
- Theoretical foundations of functional data analysis, with an introduction to linear operators
- Time series analysis
- Time series analysis : forecasting and control
- Time series analysis : nonstationary and noninvertible distribution theory
- Time series analysis and forecasting by example
- Time series analysis and forecasting by example
- Using the Weibull distribution : reliability, modeling, and inference

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