Lecture Notes in Statistics

By: JÃ¼rgen GroÃ?

Write A Review

Paperback | 25 July 2003

At a Glance

Paperback
416 Pages

Dimensions(cm)
23.5 x 15.24 x 2.54

Paperback

$249.00

or 4 interest-free payments of $62.25 with

Ships in 5 to 7 business days

In linear regression the ordinary least squares estimator plays a central role and sometimes one may get the impression that it is the only reasonable and applicable estimator available. Nonetheless, there exists a variety of alterna- tives, proving useful in specific situations. Purpose and Scope. This book aims at presenting a comprehensive survey of different point estimation methods in linear regression, along with the the- oretical background on a advanced courses level. Besides its possible use as a companion for specific courses, it should be helpful for purposes of further reading, giving detailed explanations on many topics in this field. Numerical examples and graphics will aid to deepen the insight into the specifics of the presented methods. For the purpose of self-containment, the basic theory of linear regression models and least squares is presented. The fundamentals of decision theory and matrix algebra are also included. Some prior basic knowledge, however, appears to be necessary for easy reading and understanding.

Shipping

	Standard Shipping	Express Shipping
Metro postcodes:	$9.99	$14.95
Regional postcodes:	$9.99	$14.95
Rural postcodes:	$9.99	$14.95

Orders over $79.00 qualify for free shipping.

How to return your order

At Booktopia, we offer hassle-free returns in accordance with our returns policy. If you wish to return an item, please get in touch with Booktopia Customer Care.

Additional postage charges may be applicable.

Defective items

If there is a problem with any of the items received for your order then the Booktopia Customer Care team is ready to assist you.

For more info please visit our Help Centre.

You Can Find This Book In

Non-Fiction Mathematics Probability & Statistics

This product is categorised by

Non-Fiction Mathematics Probability & Statistics

Point Estimation and Linear Regression
Fundamentals	p. 3
The Linear Regression Model	p. 33
Alternatives to Least Squares Estimation
Alternative Estimators	p. 89
Linear Admissibility	p. 213
Miscellaneous Topics
The Covariance Matrix of the Error Vector	p. 259
Regression Diagnostics	p. 293
Matrix Algebra	p. 331
Stochastic Vectors	p. 359
An Example Analysis with R	p. 369
References	p. 381
Index	p. 389
Table of Contents provided by Blackwell. All Rights Reserved.

Lecture Notes in Statistics

At a Glance

Paperback

Shipping

How to return your order

Defective items

You Can Find This Book In

More in Probability & Statistics

The Black Swan

The Impact of the Highly Improbable

Statistics and Data Handling for Biologists

A Student's Guide

Statistics and Data Handling for Biologists

A Student's Guide

Deep Learning Applications in Operations Research

Advances in Computational Collective Intelligence

Air Transportation Industry

History and Developments

Applications of Big Data and Machine Learning in Galaxy Formation and Evolution

Series in Astronomy and Astrophysics

Artificial Intelligence Assisted Structural Optimization

Attack-and-Defense Games for Control Systems

Analysis and Synthesis

Automatic Generation Of Algorithms

Advances in Metaheuristics

Back to Statistics

Tail-Aware Control Performance Assessment

Barrier Engineering

Models and Methods for Technical Safety

Collective Intelligence

The Rise of Swarm Systems and their Impact on Society

Computer Vision

Challenges, Trends, and Opportunities

The Credibility Gap

Evaluating and Improving Empirical Research in the Social Sciences

DevOps for Data Science

Chapman & Hall/CRC Data Science Series

Handbook of Disruptive Technologies

Operations, Business, Management, and Healthcare

An Integrated Approach to Modeling and Optimization in Engineering and Science

Intelligent Fatigue Statistics

Introduction to Nuclear Engineering

A Study Guide

Mathematical Analysis and its Applications

Mathematical Analysis for Engineering and Applied Sciences

Foundational and Fundamental Aspects

Multi-Criteria Decision-Making and Optimum Design with Machine Learning

A Practical Guide

Optimization Techniques and Associated Applications

Engineering Mathematics and Operations Research

Predictive Analytics and Generative AI for Data-Driven Marketing Strategies

Artificial Intelligence, Machine Learning, Data Analytics and Automation for Business Management

This product is categorised by