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Journal ArticleDOI

Multivariate Statistics: A Practical Approach

01 Jan 1990-Journal of The Royal Statistical Society Series A-statistics in Society (John Wiley & Sons, Ltd)-Vol. 153, Iss: 1, pp 112-113
About: This article is published in Journal of The Royal Statistical Society Series A-statistics in Society.The article was published on 1990-01-01. It has received 352 citations till now. The article focuses on the topics: Multivariate statistics & Multivariate analysis.
Citations
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Journal ArticleDOI
TL;DR: This paper describes a technique for building compact models of the shape and appearance of flexible objects seen in 2D images, derived from the statistics of labelled images containing examples of the objects.

973 citations

Journal ArticleDOI
TL;DR: Flow cytometry is a technique, which allows one to analyze cells rapidly and individually and permits the quantitative analysis of microbial heterogeneity, and offers many advantages over conventional measurements for both routine and more exploratory analyses of microbial properties.

875 citations

Book ChapterDOI
14 Jun 1993
TL;DR: It is described how the models can be used in local image search and give examples of their application to medical images, and how the method can be simply extended to segment 3-D objects in volume images and to track structures in image sequences.
Abstract: This paper describes a technique for building compact models of the shape and appearance of flexible objects (such as organs) seen in 2-D images The models are derived from the statistics of sets of labelled images of examples of the objects Each model consists of a flexible shape template, describing how important points of the object can vary, and a statistical model of the expected grey levels in regions around each model point The shape models are parameterised in such a way as to allow ‘legal’ configurations Such models have proved useful in a wide variety of applications We describe how the models can be used in local image search and give examples of their application to medical images We also describe how the method can be simply extended to segment 3-D objects in volume images and to track structures in image sequences

729 citations

Book
17 Feb 2006
TL;DR: An Introduction to R What Is R?
Abstract: An Introduction to R What Is R? Installing R Help and Documentation Data Objects in R Data Import and Export Basic Data Manipulation Computing with Data Organizing an Analysis Data Analysis Using Graphical Displays Introduction Initial Data Analysis Analysis Using R Simple Inference Introduction Statistical Tests Analysis Using R Conditional Inference Introduction Conditional Test Procedures Analysis Using R Analysis of Variance Introduction Analysis of Variance Analysis Using R Simple and Multiple Linear Regression Introduction Simple Linear Regression Multiple Linear Regression Analysis Using R Logistic Regression and Generalized Linear Models Introduction Logistic Regression and Generalized Linear Models Analysis Using R Density Estimation Introduction Density Estimation Analysis Using R Recursive Partitioning Introduction Recursive Partitioning Analysis Using R Scatterplot Smoothers and Generalized Additive Models Introduction Scatterplot Smoothers and Generalized Additive Models Analysis Using R Survival Analysis Introduction Survival Analysis Analysis Using R Analyzing Longitudinal Data I Introduction Analyzing Longitudinal Data Linear Mixed Effects Models Analysis Using R Prediction of Random Effects The Problem of Dropouts Analyzing Longitudinal Data II Introduction Methods for Nonnormal Distributions Analysis Using R: GEE Analysis Using R: Random Effects Simultaneous Inference and Multiple Comparisons Introduction Simultaneous Inference and Multiple Comparisons Analysis Using R Meta-Analysis Introduction Systematic Reviews and Meta-Analysis Statistics of Meta-Analysis Analysis Using R Meta-Regression Publication Bias Principal Component Analysis Introduction Principal Component Analysis Analysis Using R Multidimensional Scaling Introduction Multidimensional Scaling Analysis Using R Cluster Analysis Introduction Cluster Analysis Analysis Using R Bibliography Index A Summary appears at the end of each chapter.

591 citations


Cites background from "Multivariate Statistics: A Practica..."

  • ...4 Flury and Riedwyl (1988) report data that give various lengths measurements on 200 Swiss bank notes....

    [...]

Journal ArticleDOI
24 May 2002-Science
TL;DR: It is found that neuronal activity in this pathway encodes upcoming eye movements and that inactivating the pathway impairs sequential eye movements consistent with loss of corollary discharge without affecting single eye movements.
Abstract: It is essential to keep track of the movements we make, and one way to do that is to monitor correlates, or corollary discharges, of neuronal movement commands. We hypothesized that a previously identified pathway from brainstem to frontal cortex might carry corollary discharge signals. We found that neuronal activity in this pathway encodes upcoming eye movements and that inactivating the pathway impairs sequential eye movements consistent with loss of corollary discharge without affecting single eye movements. These results identify a pathway in the brain of the primate Macaca mulatta that conveys corollary discharge signals.

540 citations

References
More filters
Journal ArticleDOI
TL;DR: This paper describes a technique for building compact models of the shape and appearance of flexible objects seen in 2D images, derived from the statistics of labelled images containing examples of the objects.

973 citations

Journal ArticleDOI
TL;DR: Flow cytometry is a technique, which allows one to analyze cells rapidly and individually and permits the quantitative analysis of microbial heterogeneity, and offers many advantages over conventional measurements for both routine and more exploratory analyses of microbial properties.

875 citations

Book ChapterDOI
14 Jun 1993
TL;DR: It is described how the models can be used in local image search and give examples of their application to medical images, and how the method can be simply extended to segment 3-D objects in volume images and to track structures in image sequences.
Abstract: This paper describes a technique for building compact models of the shape and appearance of flexible objects (such as organs) seen in 2-D images The models are derived from the statistics of sets of labelled images of examples of the objects Each model consists of a flexible shape template, describing how important points of the object can vary, and a statistical model of the expected grey levels in regions around each model point The shape models are parameterised in such a way as to allow ‘legal’ configurations Such models have proved useful in a wide variety of applications We describe how the models can be used in local image search and give examples of their application to medical images We also describe how the method can be simply extended to segment 3-D objects in volume images and to track structures in image sequences

729 citations

Book
17 Feb 2006
TL;DR: An Introduction to R What Is R?
Abstract: An Introduction to R What Is R? Installing R Help and Documentation Data Objects in R Data Import and Export Basic Data Manipulation Computing with Data Organizing an Analysis Data Analysis Using Graphical Displays Introduction Initial Data Analysis Analysis Using R Simple Inference Introduction Statistical Tests Analysis Using R Conditional Inference Introduction Conditional Test Procedures Analysis Using R Analysis of Variance Introduction Analysis of Variance Analysis Using R Simple and Multiple Linear Regression Introduction Simple Linear Regression Multiple Linear Regression Analysis Using R Logistic Regression and Generalized Linear Models Introduction Logistic Regression and Generalized Linear Models Analysis Using R Density Estimation Introduction Density Estimation Analysis Using R Recursive Partitioning Introduction Recursive Partitioning Analysis Using R Scatterplot Smoothers and Generalized Additive Models Introduction Scatterplot Smoothers and Generalized Additive Models Analysis Using R Survival Analysis Introduction Survival Analysis Analysis Using R Analyzing Longitudinal Data I Introduction Analyzing Longitudinal Data Linear Mixed Effects Models Analysis Using R Prediction of Random Effects The Problem of Dropouts Analyzing Longitudinal Data II Introduction Methods for Nonnormal Distributions Analysis Using R: GEE Analysis Using R: Random Effects Simultaneous Inference and Multiple Comparisons Introduction Simultaneous Inference and Multiple Comparisons Analysis Using R Meta-Analysis Introduction Systematic Reviews and Meta-Analysis Statistics of Meta-Analysis Analysis Using R Meta-Regression Publication Bias Principal Component Analysis Introduction Principal Component Analysis Analysis Using R Multidimensional Scaling Introduction Multidimensional Scaling Analysis Using R Cluster Analysis Introduction Cluster Analysis Analysis Using R Bibliography Index A Summary appears at the end of each chapter.

591 citations

Journal ArticleDOI
24 May 2002-Science
TL;DR: It is found that neuronal activity in this pathway encodes upcoming eye movements and that inactivating the pathway impairs sequential eye movements consistent with loss of corollary discharge without affecting single eye movements.
Abstract: It is essential to keep track of the movements we make, and one way to do that is to monitor correlates, or corollary discharges, of neuronal movement commands. We hypothesized that a previously identified pathway from brainstem to frontal cortex might carry corollary discharge signals. We found that neuronal activity in this pathway encodes upcoming eye movements and that inactivating the pathway impairs sequential eye movements consistent with loss of corollary discharge without affecting single eye movements. These results identify a pathway in the brain of the primate Macaca mulatta that conveys corollary discharge signals.

540 citations