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[资源] Applied Spatial Data Analysis with R

We began writing this book in parallel with developing software for handling
and analysing spatial data with R (R Development Core Team, 2008). Although
the book is now complete, software development will continue, in the
R community fashion, of rich and satisfying interaction with users around the
world, of rapid releases to resolve problems, and of the usual joys and frustrations
of getting things done. There is little doubt that without pressure from
users, the development of R would not have reached its present scale, and the
same applies to analysing spatial data analysis with R.
It would, however, not be sufficient to describe the development of the
R project mainly in terms of narrowly defined utility. In addition to being a
community project concerned with the development of world-class data analysis
software implementations, it promotes specific choices with regard to how
data analysis is carried out. R is open source not only because open source
software development, including the dynamics of broad and inclusive user and
developer communities, is arguably an attractive and successful development
model.
R is also, or perhaps chiefly, open source because the analysis of empirical
and simulated data in science should be reproducible. As working researchers,
we are all too aware of the possibility of reaching inappropriate conclusions
in good faith because of user error or misjudgement. When the results of
research really matter, as in public health, in climate change, and in many
other fields involving spatial data, good research practice dictates that someone
else should be, at least in principle, able to check the results. Open source
software means that the methods used can, if required, be audited, and journalling
working sessions can ensure that we have a record of what we actually
did, not what we thought we did. Further, using Sweave1 – a tool that permits
the embedding of R code for complete data analyses in documents – throughout
this book has provided crucial support (Leisch, 2002; Leisch and Rossini

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2013-06-10 22:46:36, 9.29 M

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