- Home
- Mathematics
- Probability & Statistics
- Correspondence Analysis and Data Coding with Java and R
Correspondence Analysis and Data Coding with Java and R
List Price:
$89.99
- Availability: Confirm prior to ordering
- Branding: minimum 50 pieces (add’l costs below)
- Check Freight Rates (branded products only)
Branding Options (v), Availability & Lead Times
- 1-Color Imprint: $2.00 ea.
- Promo-Page Insert: $2.50 ea. (full-color printed, single-sided page)
- Belly-Band Wrap: $2.50 ea. (full-color printed)
- Set-Up Charge: $45 per decoration
- Availability: Product availability changes daily, so please confirm your quantity is available prior to placing an order.
- Branded Products: allow 10 business days from proof approval for production. Branding options may be limited or unavailable based on product design or cover artwork.
- Unbranded Products: allow 3-5 business days for shipping. All Unbranded items receive FREE ground shipping in the US. Inquire for international shipping.
- RETURNS/CANCELLATIONS: All orders, branded or unbranded, are NON-CANCELLABLE and NON-RETURNABLE once a purchase order has been received.
Product Details
Author:
Fionn Murtagh
Format:
Paperback
Pages:
256
Publisher:
CRC Press (September 5, 2019)
Language:
English
Audience:
Professional and scholarly
ISBN-13:
9780367392734
Weight:
12.875oz
Dimensions:
6.125" x 9.1875"
File:
TAYLORFRANCIS-TayFran_260121055423912-20260121.xml
Folder:
TAYLORFRANCIS
List Price:
$89.99
Country of Origin:
United States
Series:
Chapman & Hall/CRC Computer Science & Data Analysis
Case Pack:
10
As low as:
$85.49
Publisher Identifier:
P-CRC
Discount Code:
H
Pub Discount:
30
Imprint:
Chapman and Hall/CRC
Overview
This book introduces the theory, methods, and applications of correspondence analysis. With an emphasis on data coding, it clearly demonstrates why this technique remains important and in the eyes of many, unsurpassed as an analysis framework. Within this highly practical presentation, the author provides a theoretical overview and software in Java and R for correspondence analysis, clustering, and interpretation tools. A full chapter of case studies explores a range of applications to time-evolving data and in areas such as financial modeling, shape analysis, and the biosciences. The software and all of the data sets used in the book are available on a supporting web site.








