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Xplore: Application Guide
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Xplore: Application Guide Paperback - 2000 - 1st Edition

by W. Härdle/ Z. Hlavka/ S. Klinke

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  • Paperback

Description

Springer Verlag, 2000. Paperback. New. 1st edition. 525 pages. 9.50x6.50x1.50 inches.
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Details

  • Title Xplore: Application Guide
  • Author W. Härdle/ Z. Hlavka/ S. Klinke
  • Binding Paperback
  • Edition number 1st
  • Edition 1
  • Condition New
  • Language ENG
  • Publisher Springer Verlag, New York:
  • Date 2000
  • Features Illustrated
  • Bookseller's Inventory # x-3540675450
  • ISBN 9783540675457

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From the publisher

Most statistical applications involve computational work with data stored on a computer. The mechanics of interaction with the data is a function of the sta- tistical computing environment. This application guide is intended for slightly experienced statisticians in computer-aided data analysis who desire to learn advanced applications in various fields of statistics. The prerequisities for XploRe-the statistic computing environment-are an introductory course in statistics or mathematics. This book is designed as an e-book which means that the text contained in here is also available as an integrated document in HTML and PDF format. The reader of this application guide should therefore be familiar with the basics of Acrobat Reader and of HTML browsers in order to profit from direct computing possibilities within this document. The quantlets presented here may be used together with the academic edi- tion of XploRe (http: //www.i-xplore.de) or via the XploRe Quantlet Client (XQC) on http: //www.xplore-stat.de. The book comes together with a CD- Rom that contains the XploRe Quantlet Server (XQS) and the full Auto Pilot Support System (APSS). With this e-book bundle one may directly try the application without being dependent on a specific software version. The quantlets described in the book can be accessed via the links included All executable quantlets are denoted by the symbol . Some in the text.

First line

The purpose of the classical least squares estimation is to answer the question "How does the conditional expectation of a random variable Y, E(Y\X), depend on some explanatory variables X?" usually under some assumptions about the functional form of E(Y\X), e.g., linearity.