# A User's Guide to Principal Components.

@article{Jolliffe1991AUG, title={A User's Guide to Principal Components.}, author={Ian T. Jolliffe and J. Edward Jackson}, journal={The Statistician}, year={1991}, volume={42}, pages={76-77} }

Preface.Introduction.1. Getting Started.2. PCA with More Than Two Variables.3. Scaling of Data.4. Inferential Procedures.5. Putting It All Together-Hearing Loss I.6. Operations with Group Data.7. Vector Interpretation I : Simplifications and Inferential Techniques.8. Vector Interpretation II: Rotation.9. A Case History-Hearing Loss II.10. Singular Value Decomposition: Multidimensional Scaling I.11. Distance Models: Multidimensional Scaling II.12. Linear Models I : Regression PCA of Predictor…

## Figures and Tables from this paper

## 4,383 Citations

### STOPPING RULES IN PRINCIPAL COMPONENTS ANALYSIS: A COMPARISON OF HEURISTICAL AND STATISTICAL APPROACHES'

- Mathematics
- 1993

Approaches to determining the number of components to interpret from principal components analysis were compared. Heuristic procedures included: retaining components with eigenvalues (Xs) > 1 (i.e.,…

### Simple component analysis

- Computer Science
- 2004

The ultimate goal of simple component analysis is not to propose a method that leads automatically to a unique solution, but to develop tools for assisting the user in his or her choice of an interpretable solution.

### Interactive Principal Component Analysis

- Computer Science2017 21st International Conference Information Visualisation (IV)
- 2017

An interactive PCA view is implemented in the text visualization tool called Text Variation Explorer that allows the user to interactively study the result of PCA, and provides a better understanding of the process.

### Introductory Statistics

- Computer ScienceTechnometrics
- 2007

This book is an introduction to a form of multivariate data analysis developed in the late 1970s and 1980s by Jean–Paul Benzécri, where numerous methods are used to transform and weight raw data to put it into a form suitable for correspondence analysis.

### Statistics Toolbox User's Guide

- Mathematics
- 1998

Provide feedback about this page ttest One-sample t-test Syntax h = ttest(x) h = ttest(x,m) h = ttest(x,y) h = ttest(... Description h = ttest(x) performs a t-test of the null hypothesis that data in…

### A Practical Guide to Scientific Data Analysis

- Environmental Science
- 2009

Preface. Abbreviations. 1 Introduction: Data and it's Properties, Analytical Methods and Jargon . 1.1 Introduction. 1.2 Types of Data. 1.3 Sources of Data. 1.4 The Nature of Data. 1.5 Analytical…

### 7 - Canonical Variate Analysis and Related Methods for Reduction of Dimensionality and Graphical Representation

- Mathematics
- 2005

### Principal Component Analysis

- Computer Science
- 2003

PCA is a linear transformation that transforms the data to a new coordinate system such that the new set of variables, the principal components, are linear functions of the original variables, are uncorrelated, and the greatest variance by any projection of the data comes to lie on the first coordinate.

### GIVING MEANINGFUL INTERPRETATION TO ORDINATION AXES: ASSESSING LOADING SIGNIFICANCE IN PRINCIPAL COMPONENT ANALYSIS

- Environmental Science
- 2003

Principal component analysis (PCA) is one of the most commonly used tools in the analysis of ecological data. This method reduces the effective dimensionality of a multivariate data set by producing…

## References

SHOWING 1-4 OF 4 REFERENCES

### Principal Component Analysis

- Mathematics, GeologyInternational Encyclopedia of Statistical Science
- 1986

Introduction * Properties of Population Principal Components * Properties of Sample Principal Components * Interpreting Principal Components: Examples * Graphical Representation of Data Using…

### [Principal components analysis].

- MedicineAtencion primaria
- 1993

Only reduction data dimension could be justify the use of principal component analysis in identifying factors or components latent besides health indicators from Spanish regions, and its graphic output.

### Common Principal Components and Related Multivariate Models

- Mathematics
- 1988

Preliminaries principal component analysis relationships between matrices common practical components proportional covariance matrices partial common components and common space analysis how…

### Component Analysis versus Common Factor Analysis: Some issues in Selecting an Appropriate Procedure.

- BusinessMultivariate behavioral research
- 1990

This work discusses the key algebraic similarities and differences between principal component analysis and factor analysis, and analyzes a number of theoretical and practical issues.