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Reproducible research with R and RSt...

Gandrud, Christopher.

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Reproducible research with R and RStudio /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Reproducible research with R and RStudio // Christopher Gandrud.
作者:	Gandrud, Christopher.
出版者:	Boca Raton :CRC Press/Taylor & Francis Group, : 2014.,
面頁冊數:	xxv, 288 p. :ill. ;24 cm.
標題:	Research - Statistical methods. -
ISBN:	9781466572843 (pbk.) :

Reproducible research with R and RStudio /
Gandrud, Christopher.

Reproducible research with R and RStudio /Christopher Gandrud. - Boca Raton :CRC Press/Taylor & Francis Group,2014. - xxv, 288 p. :ill. ;24 cm. - Chapman & Hall/CRC the R series. - Chapman & Hall/CRC the R series (CRC Press).

Includes bibliographical references (p. 271-277) and index.

Preface This book has its genesis in my PhD research at the London School of Economics. I started the degree with questions about the 2008/09 financial crisis and planned to spend most of my time researching about capital adequacy requirements. But I quickly realized much of my time would actually be spent learning the day-to-day tasks of data gathering, analysis, and results presentation. After plodding through for awhile, the breaking point came while reentering results into a regression table after I had tweaked one of my statistical models, yet again. Surely there was a better way to do research that would allow me to spend more time answering my research questions. Making research reproducible for others also means making it better organized and efficient for yourself. So, my search for a better way led me straight to the tools for reproducible computational research. The reproducible research community is very active, knowledgeable and helpful. Nonetheless, I often encountered holes in this collective knowledge, or at least had no resource to bring it all together as a whole. That is my intention for this book: to bring together the skills I have picked up for actually doing and presenting computational research. Hopefully, the book along with making reproducible research more common, will save researchers hours of Googling, so they can spend more time addressing their research questions. I would not have been able to write this book without many people's advice and support. Foremost is John Kimmel, acquisitions editor at Chapman & Hall. He approached me with in Spring 2012 with the general idea and opportunity for this book.

ISBN: 9781466572843 (pbk.) :UK44.99

LCCN: 2013018868Subjects--Topical Terms:

554557
Research
--Statistical methods.

LC Class. No.: Q180.55.S7 / G36 2014

Dewey Class. No.: 001.4/2202855133

Reproducible research with R and RStudio /
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245 1 0 $a Reproducible research with R and RStudio / $c Christopher Gandrud.
260 # $a Boca Raton : $b CRC Press/Taylor & Francis Group, $c 2014.
300 $a xxv, 288 p. : $b ill. ; $c 24 cm.
490 1 0 $a Chapman & Hall/CRC the R series
504 $a Includes bibliographical references (p. 271-277) and index.
520 # $a Preface This book has its genesis in my PhD research at the London School of Economics. I started the degree with questions about the 2008/09 financial crisis and planned to spend most of my time researching about capital adequacy requirements. But I quickly realized much of my time would actually be spent learning the day-to-day tasks of data gathering, analysis, and results presentation. After plodding through for awhile, the breaking point came while reentering results into a regression table after I had tweaked one of my statistical models, yet again. Surely there was a better way to do research that would allow me to spend more time answering my research questions. Making research reproducible for others also means making it better organized and efficient for yourself. So, my search for a better way led me straight to the tools for reproducible computational research. The reproducible research community is very active, knowledgeable and helpful. Nonetheless, I often encountered holes in this collective knowledge, or at least had no resource to bring it all together as a whole. That is my intention for this book: to bring together the skills I have picked up for actually doing and presenting computational research. Hopefully, the book along with making reproducible research more common, will save researchers hours of Googling, so they can spend more time addressing their research questions. I would not have been able to write this book without many people's advice and support. Foremost is John Kimmel, acquisitions editor at Chapman & Hall. He approached me with in Spring 2012 with the general idea and opportunity for this book.
650 # 0 $a Research $x Statistical methods. $3 554557
650 # 0 $a R (Computer program language) $3 784593
830 0 $a Chapman & Hall/CRC the R series (CRC Press) $3 2070399