Open AccessBook
Statistical Analysis of Circular Data
TLDR
This book presents a meta-modelling framework for analysing two or more samples of unimodal data from von Mises distributions, and some modern Statistical Techniques for Testing and Estimation used in this study.Abstract:
Preface 1. The purpose of the book 2. Survey of contents 3. How to use the book 4. Notation, terminology and conventions 5. Acknowledgements Part I. Introduction: Part II. Descriptive Methods: 2.1. Introduction 2.2. Data display 2.3. Simple summary quantities 2.4. Modifications for axial data Part III. Models: 3.1. Introduction 3.2. Notation trigonometric moments 3.3. Probability distributions on the circle Part IV. Analysis of a Single Sample of Data: 4.1. Introduction 4.2. Exploratory analysis 4.3. Testing a sample of unit vectors for uniformity 4.4. Nonparametric methods for unimodal data 4.5. Statistical analysis of a random sample of unit vectors from a von Mises distribution 4.6. Statistical analysis of a random sample of unit vectors from a multimodal distribution 4.7. Other topics Part V. Analysis of Two or More Samples, and of Other Experimental Layouts: 5.1. Introduction 5.2. Exploratory analysis 5.3. Nonparametric methods for analysing two or more samples of unimodal data 5.4. Analysis of two or more samples from von Mises distributions 5.5. Analysis of data from more complicated experimental designs Part VI. Correlation and Regression: 6.1. Introduction 6.2. Linear-circular association and circular-linear association 6.3. Circular-circular association 6.4. Regression models for a circular response variable Part VII. Analysis of Data with Temporal or Spatial Structure: 7.1. Introduction 7.2. Analysis of temporal data 7.3. Spatial analysis Part VIII. Some Modern Statistical Techniques for Testing and Estimation: 8.1. Introduction 8.2. Bootstrap methods for confidence intervals and hypothesis tests: general description 8.3. Bootstrap methods for circular data: confidence regions for the mean direction 8.4. Bootstrap methods for circular data: hypothesis tests for mean directions 8.5. Randomisation, or permutation, tests Appendix A. Tables Appendix B. Data sets References Index.read more
Citations
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Measuring phase synchrony in brain signals
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Filtering via Simulation: Auxiliary Particle Filters
Michael K. Pitt,Neil Shephard +1 more
TL;DR: This article analyses the recently suggested particle approach to filtering time series and suggests that the algorithm is not robust to outliers for two reasons: the design of the simulators and the use of the discrete support to represent the sequentially updating prior distribution.
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CircStat: A Matlab Toolbox for Circular Statistics
TL;DR: The CircStat toolbox for MATLAB is implemented which provides methods for the descriptive and inferential statistical analysis of directional data and analyzes a dataset from neurophysiology to demonstrate the capabilities of the Circstat toolbox.
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Discrete fixed-resolution representations in visual working memory
Weiwei Zhang,Steven J. Luck +1 more
TL;DR: It is shown that, when presented with more than a few simple objects, human observers store a high-resolution representation of a subset of the objects and retain no information about the others.
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Local Regression and Likelihood
TL;DR: The Origins of Local Regression, Fitting with LOCFIT, and Optimizing local Regression methods.
References
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Book
Statistical Analysis of Spherical Data
TL;DR: This is the first comprehensive, yet clearly presented, account of statistical methods for analysing spherical data and the emphasis is on applications rather than theory, with the statistical methods being illustrated throughout the book by data examples.
Journal ArticleDOI
Statistical Analysis of Spherical Data.
TL;DR: In this paper, the authors present a unified and up-to-date account of statistical analysis of spherical data for practical use, focusing on applications rather than theory, with the statistical methods being illustrated throughout the book by data examples.