Open AccessBook
Modern applied statistics with S-Plus
TLDR
This book is a guide to using S-Plus to perform statistical analyses and provides both an introduction to the use of S- Plus and a course in modern statistical methods.Abstract:
S-Plus is a powerful environment for statistical and graphical analysis of data. It provides the tools to implement many statistical ideas which have been made possible by the widespread availability of workstations having good graphics and computational capabilities. This book is a guide to using S-Plus to perform statistical analyses and provides both an introduction to the use of S-Plus and a course in modern statistical methods. All data sets and S-Plus functions used are supplied with the book on a diskette.read more
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Estimating Continuous Distributions in Bayesian Classifiers
George H. John,Pat Langley +1 more
TL;DR: This paper abandon the normality assumption and instead use statistical methods for nonparametric density estimation for kernel estimation, which suggests that kernel estimation is a useful tool for learning Bayesian models.
Book
Model-based Geostatistics
TL;DR: An overview of model-based geostatistics can be found in this paper, where a generalized linear model is proposed for estimating geometrical properties of geometrically constrained data.
Journal ArticleDOI
Global land cover classification at 1 km spatial resolution using a classification tree approach
TL;DR: In this paper, a 1km spatial resolution land cover classification using data for 1992-1993 from the Advanced Very High Resolution Radiometer (AVHRR) is presented. But the approach taken involved a hierarchy of pair-wise class trees where a logic based on vegetation form was applied until all classes were depicted.
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Machine Learning for the Detection of Oil Spills in Satellite Radar Images
TL;DR: This case study relates issues as problem formulation, selection of evaluation measures, and data preparation to properties of the oil spill application, such as its imbalanced class distribution, that are shown to be common to many applications.
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Changes in fire and climate in the eastern iberian peninsula (mediterranean basin)
TL;DR: In this paper, the authors analyzed the trend in fire number and area burned in the eastern Iberian Peninsula, and then, to what extent is the inter-annual variability of fires determined by climatic factors.
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Robust Locally Weighted Regression and Smoothing Scatterplots
TL;DR: Robust locally weighted regression as discussed by the authors is a method for smoothing a scatterplot, in which the fitted value at z k is the value of a polynomial fit to the data using weighted least squares, where the weight for (x i, y i ) is large if x i is close to x k and small if it is not.
Book
Statistical Models in S
John M. Chambers,Trevor Hastie +1 more
TL;DR: The interactive data analysis and graphics language S has become a popular environment for both data analysts and research statisticians, but a common complaint has concerned the lack of statistical modeling tools, such as those provided by GLIM© or GENSTAT©.
Book
Graphical Methods for Data Analysis
TL;DR: This paper presents a meta-modelling framework for developing and assessing regression models for multivariate and multi-dimensional data distributions and describes the distribution of a set of data.
Journal ArticleDOI
Consistent Nonparametric Regression
TL;DR: In this article, a sequence of probability weight functions defined in terms of nearest neighbors is constructed and sufficient conditions for consistency are obtained, which are applied to verify the consistency of the estimators of the various quantities discussed above and the consistency in Bayes risk of the approximate Bayes rules.