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Optimal subset selection: multiple regression, interdependence, and optimal network algorithms

Author: David E Boyce; Alexandre Faire; R Weischedel
Publisher: Berlin, New York, Springer-Verlag, 1974.
Series: Lecture notes in economics and mathematical systems, 103.
Edition/Format:   eBook : Document : EnglishView all editions and formats
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Additional Physical Format: Print version:
Boyce, David E.
Optimal subset selection: multiple regression, interdependence, and optimal network algorithms.
Berlin, New York, Springer-Verlag, 1974
(DLC) 74018097
(OCoLC)1046064
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: David E Boyce; Alexandre Faire; R Weischedel
OCLC Number: 567675578
Reproduction Notes: Electronic reproduction. [S.l.] : HathiTrust Digital Library, 2010. MiAaHDL
Description: 1 online resource (x, 187 pages).
Details: Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002.
Contents: 1.1 Orientation and Objective.- 1.2 Organization.- 2. Optimal Regression Analysis.- 2.1 Introduction.- 2.2 Description of the Algorithm.- 2.2.1 General Algorithm.- 2.2.2 Optimal Regression Algorithm.- 2.3 Strategies in Using the Program.- 2.3.1 Alternate Ways of Stopping the Program.- 2.3.2 Options for Using the Program.- 2.4 Related Multiple Regression Programs.- 2.5 Case Studies of Optimal vs. Stepwise Regression.- 2.6 Suggestions for a Strategy for Using the Program.- 2.7 Order and Detailed Description of Input Card Types.- 2.7.1 Title.- 2.7.2 Problem Definition.- 2.7.3 Equations Desired.- 2.7.4 Iteration Limits.- 2.7.5 Equations Previously Processed.- 2.7.6 Confidence Limits on F-ratios.- 2.7.7 Confidence Limits on t-tests.- 2.7.8 Lower Tolerance Limits on Durbin-Watson d-statistic.- 2.7.9 Upper Tolerance Limits on Durbin-Watson d-statistic.- 2.7.10 Variables to be Forced.- 2.7.11 Format of Data.- 2.7.12 Output Options.- 2.7.13 Labels for Variables.- 2.7.14 Subset of Original Variables.- 2.7.15 Data Deck.- 2.7.16 Unconditional Thresholds.- 2.7.17 Information from Previous Jobs.- 2.7.18 WARNING.- 2.8 Several Analyses on Different Sets of Data or the Same Data.- 2.9 Output of the Program.- 2.10 Machine Dependent Program Features and Suggestions for Modification.- 2.11 Description of Program by Subroutine.- 2.11.1 MAIN.- 2.11.2 SETUP.- 2.11.3 STAGE2.- 2.11.4 PRIMR.- 2.11.5 STAGE4.- 2.11.6 CHKVAR.- 2.11.7 STAGE8.- 2.11.8 FMAXOD.- 2.11.9 OUTATl.- 2.11.10 OUTATM.- 2.11.11 CONDTH.- 2.11.12 PLACE(B,C).- 2.11.13 PIVOTR(ORIG, STORE, NG, INVRNO, IDIM,IDONE).- 2.11.14 RITOUT(ATRIX, INOUT, NEL).- 2.11.15 RESET.- 2.11.16 OUTPUT.- 2.11.17 STG13A.- 2.11.18 STG4A.- 2.11.19 STG4AB.- 2.12 Definitions of the Square of the Multiple Correlation Coefficient.- 3. Interdependence Analysis.- 3.1 Introduction.- 3.2 Interdependence Analysis Algorithm.- 3.2.1 Pivot Operations.- 3.2.2 Description of the Algorithm.- 3.3 Example of Interdependence Analysis.- 3.4 Suggestions for a Strategy for Using the Program.- 3.5 Order and Detailed Description of Input Card Types.- 3.5.1 Title Card.- 3.5.2 Problem Definition.- 3.5.3 Values of N.- 3.5.4 Sets Previously Processed.- 3.5.5 Iteration Limits.- 3.5.6 Variables to be Forced.- 3.5.7 Format of Data.- 3.5.8 Output Options.- 3.5.9 Data Deck.- 3.5.10 Unconditional Thresholds.- 3.5.11 Information from Previous Jobs.- 3.5.12 WARNING.- 3.6 Output of the Program.- 3.7 Machine Dependent Program Features and Suggestions for Modification.- 3.8 Description of the Program by Subroutine.- 3.8.1 MAIN.- 3.8.2 SETUP.- 3.8.3 STAGE2.- 3.8.4 PRIMR.- 3.8.5 STAGE4.- 3.8.6 CHKVAR.- 3.8.7 STAGE8.- 3.8.8 FMAXOD.- 3.8.9 OUTATl.- 3.8.10 OUTATM.- 3.8.11 CONDTH.- 3.8.12 PLACE(B,C).- 3.8.13 PIVOTR(ORIG, STORE, NG, INVRNO, IDIM, IDONE).- 3.8.14 RITOUT(ATRIX, INOUT, NEL).- 3.8.15 RESET.- 3.8.16 OUTPUT.- 3.8.17 STG13A.- 3.8.18 STG4A.- 3.8.19 STG4AB.- 4. Optimal Network Analysis.- 4.1 Introduction.- 4.2 Optimal Network Algorithm.- 4.2.1 Minimum Path and Minimum Spanning Tree Algorithms.- 4.2.2 Description of the Algorithm.- 4.3 Examples of Optimal Network Analysis.- 4.4 Suggestions for a Strategy for Using the Program.- 4.5 Order and Detailed Description of Input Card Types.- 4.5.1 Title.- 4.5.2 Problem Definition.- 4.5.3 Budget Constraints.- 4.5.4 Iteration Limits.- 4.5.5 Networks Previously Processed.- 4.5.6 Links to be Forced.- 4.5.7 Output Options.- 4.5.8 Format of Links.- 4.5.9 Deck of Links.- 4.5.10 Unconditional Thresholds.- 4.5.11 Networks from Previous Jobs.- 4.5.12 WARNING.- 4.6 Output of the Program.- 4.7 Machine Dependent Features and Suggestions for Modification.- 4.8 Description of the Program by Subroutine.- 4.8.1 MAIN.- 4.8.2 SETUP.- 4.8.3 STAGE2.- 4.8.4 STAJ4A.- 4.8.5 Arrays and Variables with Same Definitions Throughout Remaining Subroutines.- 4.8.6 STG4AB.- 4.8.7 STAGE4.- 4.8.8 STAGE6(NOYES).- 4.8.9 STAGE8.- 4.8.10 CHKVAR.- 4.8.11 FMAXOD.- 4.8.12 STAJ16.- 4.8.13 STAJ17.- 4.8.14 STAJ18.- 4.8.15 STG13A.- 4.8.16 OUTPUT.- 4.8.17 RESET.- 4:8.18 CONECT(M1, M2).- 4.8.19 SPAN.- 4.8.20 MINDIS.- 4.8.21 LNKOUT(JP, KP, DP, PP, JPRINT).- 4.8.22 LINKIN(J, K, S, D, P, IPRINT).- 4.8.23 STAJ6B.
Series Title: Lecture notes in economics and mathematical systems, 103.
Responsibility: [by] D.E. Boyce, A. Farhi [and] R. Weischedel.
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