Applied Multivariate Statistical Analysis

  title={Applied Multivariate Statistical Analysis},
  author={Charles E. Heckler},
  pages={517 - 517}
  • C. Heckler
  • Published 1 November 2005
  • Environmental Science
  • Technometrics
Cressie, N. A. C. (1993), Statistics for Spatial Data (rev. ed.), New York: Wiley. Diggle, P. J. (1983), Statistical Analysis of Spatial Point Patterns, London: Academic Press. Katti, S. K. (1986), Review of Statistical Analysis of Spatial Point Patterns and Spatial Statistics, by P. J. Diggle, and B. D. Ripley, Journal of the American Statistical Association, 81, 263–264. Ripley, B. D. (1981), Spatial Statistics, New York: Wiley. (1986), Review of Statistical Analysis of Spatial Point Patterns… 
Applied Univariate, Bivariate, and Multivariate Statistics
Description: A clear and efficient balance between theory and applications of statistical modeling techniques in the social and behavioral sciences Written as a general and accessible introduction,
Spatial Clustering Using the Likelihood Function
This paper proposes a method to spatially cluster similar observations based on their likelihoods because the geographic or spatial location of the observations can be incorporated into the likelihood of the multivariate normal distribution through the variance-covariance matrix.
A Multivariate Subgroup Rationality Test
Abstract In one of our recent articles (Holmes, D. S., Mergen, A. E. (2003). Testing rationality of subgroups in multivariate control charts. In: The 2003 Northeast Decision Sciences Institute
Book Review: Computer-Aided Multivariate Analysis (4th ed.)
This book offers a concise and well-organized introduction to multivariate statistical analysis methods. For applied researchers who need a ‘‘quick start’’ to learning these methods, this book would
A S A S R Macro for the Multivariate Extension of the Kruskal-Wallis Test Including Multiple Comparisons : Randomization and Z 2 Criteria 1
In a multi-group experimental design where interest is in a univariate response, the nonparametric Kruskal-Wallis test [Kniskal and Wallis (1952)] provides a potentially more powerful alternative to
Generalized Linear Latent Variable Models for Repeated Measures of Spatially Correlated Multivariate Data
A flexible class of generalized linear latent variable models for multivariate spatial-temporal data is developed using a Monte Carlo EM algorithm and a novel way to automatically adjust the Monte Carlo sample size is used.
Bayesian single change point detection in a sequence of multivariate normal observations
A Bayesian method is used to see whether there are changes of mean, covariance, or both at an unknown time point in a sequence of independent multivariate normal observations. Noninformative priors
SSN: An R package for spatial statistical modeling on stream networks
The SSN package for R provides a set of functions for importing, simulating, and modeling of stream network data, including diagnostics and prediction, and traditional models that use Euclidean distance and simple random effects are included.
A Comparison of Hierarchical Methods for Clustering Functional Data
A simulation study compares the performance of four major hierarchical methods for clustering functional data and yields concrete suggestions to future researchers to determine the best method for clustered their functional data.
Data augmentation for a Bayesian spatial model involving censored observations
Spatial environmental data sometimes include below detection limit observations (i.e., censored values reported as less than a level of detection). Historically, the most common practice for analysis


Combining Pattern Classifiers: Methods and Algorithms
  • S. Bagui
  • Environmental Science
  • 2005
This chapter discusses the development of the Spatial Point Pattern Analysis Code in S–PLUS, which was developed in 1993 by P. J. Diggle and D. C. Griffith.
A Casebook for Spatial Statistical Data Analysis
This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data and attempts to target applied statisticians and biomedical researchers in industry, public health organizations, contract research organizations, and academia.
Statistical Analysis of Spatial Point Patterns
This book contains things I have never seen in other introductory statistics textbooks, such as the first names of Bonferroni, Venn, and Likert, and a photograph of George Gallup.
Slicing Regression: A Link-Free Regression Method
Slicing Regression: A Link-Free Regression M e t h o d Author(s): Naihua Duan and K e r - C h a u L i S o u r c e : The Annals of Statistics, V o l . 19, N o . 2 ( T u n . , 1991), p p . 5 0 5 - 5 3
A note on tests of significance in multivariate analysis
Multivariate generalizations . In multivariate statistical analysis, common terms such as variances and correlation coefficients have received certain generalizations. Wilks (7) has called the
A User's Guide to Principal Components.
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.
Multivariate Statistical Methods
This book is well intentioned for science majors, but it seems to miss the mark by being overly complicated with the unnecessary use of calculus on one hand and the recommendation of some poor statistical techniques on the other hand.
The varimax criterion for analytic rotation in factor analysis
An analytic criterion for rotation is defined. The scientific advantage of analytic criteria over subjective (graphical) rotational procedures is discussed. Carroll's criterion and the quartimax