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Springer series in statistics
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The series ** Springer series in statistics** represents a set of related resources, especially of a specified kind, found in **University of Liverpool**.

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Springer series in statistics
Resource Information

The series

**Springer series in statistics**represents a set of related resources, especially of a specified kind, found in**University of Liverpool**.- Label
- Springer series in statistics

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- Springer series in statistics, 200
- Springer series in statistics, 272.
- Springer series in statistics, 297
- Springer series in statistics, 298
- Springer series in statistics, Perspectives in statistics
- Springer series in statistics, Probability and its applications
- Springer series in statistics, v. 199
- A comparison of the bayesian and frequentist approaches to estimation
- Bayesian and frequentist regression methods
- Bayesian reliability
- Bayesian reliability
- Comparing distributions
- Design and analysis of computer experiments
- Design of observational studies
- Dynamic data analysis : modeling data with differential equations
- Dynamic mixed models for familial longitudinal data
- Elements of nonlinear time series analysis and forecasting
- Functional data analysis
- Indirect sampling
- Inequalities : theory of majorization and its applications
- Introduction to empirical processes and semiparametric inference
- Introduction to nonparametric estimation
- Introduction to variance estimation
- Life distributions : structure of nonparametric, semiparametric, and parametric families
- Linear and generalized linear mixed models and their applications
- Linear models and generalizations : least squares and alternatives
- Longitudinal categorical data analysis
- Maximum penalized likelihood estimation
- Model-based geostatistics
- Modeling discrete time-to-event data
- Models for discrete longitudinal data
- Modern multidimensional scaling : theory and applications
- Monte carlo and quasi-monte carlo sampling
- Multiple testing procedures with applications to genomics
- Multiscale modeling : a Bayesian perspective
- Multivariate analysis with LISREL
- Non-negative matrices and Markov chains
- Nonparametric functional data analysis : theory and practice
- Permutation methods : a distance function approach
- Permutation, parametric and bootstrap tests of hypotheses
- Principles and theory for data mining and machine learning
- Prior processes and their applications : nonparametric bayesian estimation
- Recursive partitioning and applications
- Semiparametric and nonparametric methods in econometrics
- Semiparametric theory and missing data
- Shrinkage estimation
- Simulation and inference for stochastic differential equations : with R examples
- Simulation and inference for stochastic differential equations : with r examples
- Spatial statistics and modeling
- Spectral analysis of large dimensional random matrices
- Statistical analysis of environmental space-time processes
- Statistical analysis of network data : methods and models
- Statistical analysis with measurement error or misclassification : strategy, method and application
- Statistical decision theory : estimation, testing, and selection
- Statistical decision theory : estimation, testing, and selection
- Statistical learning from a regression perspective
- Statistical learning from a regression perspective
- Statistics for high-dimensional data : methods, theory and applications
- Statistics for high-dimensional data : methods, theory and applications
- Stochastic orders
- Targeted learning : causal inference for observational and experimental data
- The Burrows-Wheeler transform : data compression, suffix arrays, and pattern matching
- The elements of statistical learning : data mining, inference, and prediction
- The linear model and hypothesis : a general unifying theory

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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.liverpool.ac.uk/resource/PY4RSP5X8iY/" typeof="Series http://bibfra.me/vocab/lite/Series"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.liverpool.ac.uk/resource/PY4RSP5X8iY/">Springer series in statistics</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.liverpool.ac.uk/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.liverpool.ac.uk/">University of Liverpool</a></span></span></span></span></div>

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`<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.liverpool.ac.uk/resource/PY4RSP5X8iY/" typeof="Series http://bibfra.me/vocab/lite/Series"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.liverpool.ac.uk/resource/PY4RSP5X8iY/">Springer series in statistics</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.liverpool.ac.uk/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.liverpool.ac.uk/">University of Liverpool</a></span></span></span></span></div>`