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Titlebook: Optimal Subset Selection; Multiple Regression, David E. Boyce,A. Farhi,R. Weischedel Book 1974 Springer-Verlag Berlin · Heidelberg 1974 Cou

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书目名称Optimal Subset Selection
副标题Multiple Regression,
编辑David E. Boyce,A. Farhi,R. Weischedel
视频videohttp://file.papertrans.cn/703/702933/702933.mp4
丛书名称Lecture Notes in Economics and Mathematical Systems
图书封面Titlebook: Optimal Subset Selection; Multiple Regression, David E. Boyce,A. Farhi,R. Weischedel Book 1974 Springer-Verlag Berlin · Heidelberg 1974 Cou
描述In the course of one‘s research, the expediency of meeting contractual and other externally imposed deadlines too often seems to take priority over what may be more significant research findings in the longer run. Such is the case with this volume which, despite our best intentions, has been put aside time and again since 1971 in favor of what seemed to be more urgent matters. Despite this delay, to our knowledge the principal research results and documentation presented here have not been superseded by other publications. The background of this endeavor may be of some historical interest, especially to those who agree that research is not a straightforward, mechanistic process whose outcome or even direction is known in ad­ vance. In the process of this brief recounting, we would like to express our gratitude to those individuals and organizations who facilitated and supported our efforts. We were introduced to the Beale, Kendall and Mann algorithm, the source of all our efforts, quite by chance. Professor Britton Harris suggested to me in April 1967 that I might like to attend a CEIR half-day seminar on optimal regression being given by Professor M. G. Kendall in Washington. D. C
出版日期Book 1974
关键词Counting; algorithms; calculus; equation; variable
版次1
doihttps://doi.org/10.1007/978-3-642-46311-2
isbn_softcover978-3-540-06957-7
isbn_ebook978-3-642-46311-2Series ISSN 0075-8442 Series E-ISSN 2196-9957
issn_series 0075-8442
copyrightSpringer-Verlag Berlin · Heidelberg 1974
The information of publication is updating

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Optimal Regression Analysis,provide guidance in specifying which variables to include. Often, however, several variables are available for measuring a particular attribute, and little basis exists for a clear-cut choice among them. Such situations arise frequently in the social sciences, and often also in engineering.
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Book 1974at may be more significant research findings in the longer run. Such is the case with this volume which, despite our best intentions, has been put aside time and again since 1971 in favor of what seemed to be more urgent matters. Despite this delay, to our knowledge the principal research results an
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0075-8442 ty over what may be more significant research findings in the longer run. Such is the case with this volume which, despite our best intentions, has been put aside time and again since 1971 in favor of what seemed to be more urgent matters. Despite this delay, to our knowledge the principal research
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