Morphometrics With R (use R!)
by Julien Claude /
2008 / English / PDF
3.2 MB Download
This book aims to explain how to use R to perform morphometrics.
Morpho- tric analysis is the study of shape and size variations and
covariations and their covariations with other variables.
Morphometrics is thus deeply rooted within stat- tical sciences.
While most applications concern biology, morphometrics is becoming
common tools used in archeological, palaeontological, geographical,
or medicine disciplines. Since the recent formalizations of some of
the ideas of predecessors, such as D’arcy Thompson, and thanks to
the development of computer techno- gies and new ways for
appraising shape changes and variation, morphometrics have
undergone, and are still undergoing, a revolution. Most techniques
dealing with s- tistical shape analysis have been developed in the
last three decades, and the number of publications using
morphometrics is increasing rapidly. However, the majority of these
methods cannot be implemented in available software and therefore
prosp- tive students often need to acquire detailed knowledge in
informatics and statistics before applying them to their data. With
acceleration in the accumulation of me- ods accompanying the
emerging science of statistical shape analysis, it is becoming
important to use tools that allow some autonomy. R easily helps
ful?ll this need. Risalanguage andenvironment
forstatisticalcomputingandgraphics. Although there is an increasing
number of computer applications that perform morphometrics, using R
has several advantages that confer to users considerable power and
possible new horizons in a world that requires rapid adaptability.
This book aims to explain how to use R to perform morphometrics.
Morpho- tric analysis is the study of shape and size variations and
covariations and their covariations with other variables.
Morphometrics is thus deeply rooted within stat- tical sciences.
While most applications concern biology, morphometrics is becoming
common tools used in archeological, palaeontological, geographical,
or medicine disciplines. Since the recent formalizations of some of
the ideas of predecessors, such as D’arcy Thompson, and thanks to
the development of computer techno- gies and new ways for
appraising shape changes and variation, morphometrics have
undergone, and are still undergoing, a revolution. Most techniques
dealing with s- tistical shape analysis have been developed in the
last three decades, and the number of publications using
morphometrics is increasing rapidly. However, the majority of these
methods cannot be implemented in available software and therefore
prosp- tive students often need to acquire detailed knowledge in
informatics and statistics before applying them to their data. With
acceleration in the accumulation of me- ods accompanying the
emerging science of statistical shape analysis, it is becoming
important to use tools that allow some autonomy. R easily helps
ful?ll this need. Risalanguage andenvironment
forstatisticalcomputingandgraphics. Although there is an increasing
number of computer applications that perform morphometrics, using R
has several advantages that confer to users considerable power and
possible new horizons in a world that requires rapid adaptability.