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For more information about our e-books, e-learning products, CDs, and hard-copy books, visit the SAS Publishing Web site at /publishing or call 1-80. Smoothing parameter jmp 9 graph builder software#1st printing, March 2012 2nd printing, July 2012 3rd printing, November 2012 SAS® Publishing provides a complete selection of books and electronic products to help customers use SAS software to its fullest potential. SAS Institute Inc., SAS Campus Drive, Cary, North Carolina 27513. government is subject to the Agreement with SAS Institute and the restrictions set forth in FAR 52.227-19, Commercial Computer Software-Restricted Rights (June 1987). Government Restricted Rights Notice: Use, duplication, or disclosure of this software and related documentation by the U.S. Your support of others’ rights is appreciated. Please purchase only authorized electronic editions and do not participate in or encourage electronic piracy of copyrighted materials. The scanning, uploading, and distribution of this book via the Internet or any other means without the permission of the publisher is illegal and punishable by law. For a Web download or e-book: Your use of this publication shall be governed by the terms establishedīy the vendor at the time you acquire this publication. Transmitted, in any form or by any means, electronic, mechanical, photocopying, or otherwise, without the prior written permission of the publisher, SAS Institute Inc. For a hard-copy book: No part of this publication may be reproduced, stored in a retrieval system, or Produced in the United States of America. JMP® 10 Quality and Reliability Methods Copyright © 2012, SAS Institute Inc., Cary, NC, USA ISBN 978-1-61290-199-2 All rights reserved. Smoothing parameter jmp 9 graph builder manual#The correct bibliographic citation for this manual is as follows: SAS Institute Inc. JMP, A Business Unit of SAS SAS Campus Drive Cary, NC 27513 The result will be one set of parameters.Quality and Reliability Methods “The real voyage of discovery consists not in seeking new landscapes, but in having new eyes.” Marcel Proust When a parameter is shared, a single parameter value is calculated for all datasets When a parameter is not shared, a separate parameter value is calculated for each dataset.Ī further alternative is to use Mathematics:Average Multiple Curves to produce a single new dependent dataset and fit this dataset. Because datasets remain distinct, they may or may not "share" parameter values during the fit process. Simultaneous perform curve fitting on multiple datasets. Global Fit (Available only in Nonlinear Curve Fit).The reports are output to different worksheets.Īll input datasets are concatenated and fitted as one curve. The input datasets are fitted separately. The reports are consolidated into one sheet. ![]() There are three options for the multiple datasets fit. Multi-Data Fit Mode control is availble for switching between Concatenate/Independent fitting for multiple datasets. ![]() Alternately, you can perform global fitting with shared parameters or perform a concatenated fit which combines replicate data into a single dataset prior to fitting.įirst you can click the triangle button next to Input Data to add multiple datasets to fitting dialog. Smoothing parameter jmp 9 graph builder how to#3.112 FAQ-654 How to fit multiple datasets?ĭo you have multiple datasets that you would like to fit simultaneously? With Origin, you can fit each dataset separately and output results in separate reports or in a consolidated report. ![]()
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