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References

Published online by Cambridge University Press:  21 September 2018

Fred L. Bookstein
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University of Washington
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A Course in Morphometrics for Biologists
Geometry and Statistics for Studies of Organismal Form
, pp. 494 - 505
Publisher: Cambridge University Press
Print publication year: 2018

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References

Allen, B., Curlew, B., and Popović, A.. The space of human body shapes: Reconstruction and parameterization from range scans. ACM SIGGRAPH 2003, July 2003. ACM.CrossRefGoogle Scholar
Andersen, P. K., and Skovgaard, L. T.. Regression with Linear Predictors. New York: Springer, 2010.CrossRefGoogle Scholar
Anderson, D. R. Model Based Inference in the Life Sciences: A Primer on Evidence. New York: Springer, 2008.CrossRefGoogle Scholar
Anderson, G. W., Guionnet, A., and Zeitouni, O.. An Introduction to Random Matrices. Cambridge: Cambridge University Press, 2010.Google Scholar
Anderson, T. W. Asymptotic theory for principal component analysis. Annals of Mathematical Statistics 4:122148, 1963.Google Scholar
Anderson, T. W. An Introduction to Multivariate Statistical Analysis. New York: Wiley, 1984.Google Scholar
Anson, B. J. An Atlas of Human Anatomy. Philadelphia: W. B. Saunders Company, 1950. Second edition, 1963.Google Scholar
Arias, E. United States Life Tables, 2003. National Vital Statistics Reports 54:14, 2006.Google Scholar
Bachelier, M. L. Théorie de la Spéculation. Paris: Gauthier-Villard, 1900.CrossRefGoogle Scholar
Ball, P. The Self-Made Tapestry: Pattern Formation in Nature. Oxford University Press, 1999.Google Scholar
Ball, P. Patterns in Nature: Why the Natural World Looks the Way It Does. University of Chicago Press, 2016.CrossRefGoogle Scholar
Berta, A., ed. Whales, Dolphins, and Porpoises. A Natural History and Species Guide. University of Chicago Press, 2015.CrossRefGoogle Scholar
Biegert, J. Der Formwandel des Primatenschadels. Gegenbaurs Morphologisches Jahrbuch 98:77199, 1957.Google Scholar
Blackith, R. E., and Reyment, R. A.. Multivariate Morphometrics. Academic Press, 1971.Google Scholar
Blalock, H. M., Jr. Causal Inferences in Nonexperimental Research. University of North Carolina Press, 1964.Google Scholar
Boas, F. The horizontal plane of the skull and the general problem of the comparison of variable forms. Science 21:862863, 1905.CrossRefGoogle ScholarPubMed
Bollen, K. A. Structural Equations with Latent Variables. Wiley-Interscience, 1989.CrossRefGoogle Scholar
Bookstein, F. L. The Measurement of Biological Shape and Shape Change. Lecture Notes in Biomathematics, vol. 24. Springer-Verlag, 1978.CrossRefGoogle Scholar
Bookstein, F. L. The geometry of craniofacial growth invariants. American Journal of Orthodontics 83:221234, 1983.CrossRefGoogle ScholarPubMed
Bookstein, F. L. Tensor biometrics for changes in cranial shape. Annals of Human Biology 11:413437, 1984.CrossRefGoogle ScholarPubMed
Bookstein, F. L. Principal warps: Thin-plate splines and the decomposition of deformations. IEEE Transactions on Pattern Analysis and Machine Intelligence 11:567– 585, 1989.Google Scholar
Bookstein, F. L. Morphometric Tools for Landmark Data: Geometry and Biology. Cambridge University Press, 1991.Google Scholar
Bookstein, F. L., and Green, W. D. K.. A feature space for edgels in images with landmarks. Journal of Mathematical Imaging and Vision 3:231261, 1993.CrossRefGoogle Scholar
Bookstein, F. L. Landmark methods for forms without landmarks: Localizing group differences in outline shape. Medical Image Analysis 1:225243, 1997.Google Scholar
Bookstein, F. L., Schaefer, K., Prossinger, H., Seidler, H., Fieder, M., Stringer, C., Weber, G., Arsuaga, J., Slice, D., Rohlf, F. J., Recheis, W., Mariam, A., and Marcus, L.. Comparing frontal cranial profiles in archaic and modern Homo by morphometric analysis. The Anatomical Record – The New Anatomist 257:217224, 1999.3.0.CO;2-W>CrossRefGoogle ScholarPubMed
Bookstein, F. L. Creases as local features of deformation grids. Medical Image Analysis 4:93110, 2000.Google Scholar
Bookstein, F. L.Voxel-based morphometry” should never be used with imperfectly registered images. NeuroImage NIMG.2001.0770, 14:14541462, 2001.CrossRefGoogle Scholar
Bookstein, F. L., Sampson, P. D., Streissguth, A. P., and Connor, P. D.. Geometric morphometrics of corpus callosum and subcortical structures in the fetal-alcohol-affected brain. Teratology 64:432, 2001.CrossRefGoogle ScholarPubMed
Bookstein, F. L., and Green, W. D. K.. User’s Manual, EWSH3.19. 102 pages. ftp://brainmap.stat.washington.edu/edgewarp/manual/, posted March 2002.Google Scholar
Bookstein, F. L., Streissguth, A., Sampson, P., Connor, P., and Barr, H.. Corpus callosum shape and neuropsychological deficits in adult males with heavy fetal alcohol exposure. NeuroImage 15:233251, 2002a.CrossRefGoogle ScholarPubMed
Bookstein, F. L., Sampson, P. D., Connor, P. D., and Streissguth, A. P.. The midline corpus callosum is a neuroanatomical focus of fetal alcohol damage. The Anatomical Record – The New Anatomist 269:162174, 2002b.Google Scholar
Bookstein, F. L., Gunz, P., Mitteröcker, P., Prossinger, H., Schäfer, K., and Seidler, H.. Cranial integration in Homo: Singular warps analysis of the midsagittal plane in ontogeny and evolution. Journal of Human Evolution 44:167187, 2003.Google Scholar
Bookstein, F. L., and Mardia, K. V.. The five components of directional asymmetry. Pp. 3540 in Aykroyd, R. et al., eds., Stochastic Geometry, Biological Structure, and Images. Department of Statistics, University of Leeds, 2003.Google Scholar
Bookstein, F. L. After landmarks. Pp. 4971 in Slice, D. E., ed., Modern Morphometrics in Physical Anthropology. Kluwer Academic Publishers, New York, 2004.Google Scholar
Bookstein, F. L. Morphometrics and computed homology: An old theme revisited. Pp. 6981 in MacLeod, N., ed., Proceedings of a Symposium on Algorithmic Approaches to the Identification Problem in Systematics, Museum of Natural History, London, 2007.Google Scholar
Bookstein, F. L., Connor, P. D., Huggins, J. E., Barr, H. M., Covell, K. D., and Streissguth, A. P.. Many infants prenatally exposed to high levels of alcohol show one particular anomaly of the corpus callosum. Alcoholism: Clinical and Experimental Research 31:868879, 2007.CrossRefGoogle ScholarPubMed
Bookstein, F. L. Measurement, explanation, and biology: Lessons from a long century. Biological Theory 4:620, 2009a.CrossRefGoogle Scholar
Bookstein, F. L. How quantification persuades when it persuades. Biological Theory 4:132147, 2009b.Google Scholar
Bookstein, F. L. For isotropic offset normal shape distributions, covariance distance is proportional to Procrustes distance. Pp. 4751 in Gusnanto, A., Mardia, K. V., and Fallaize, C., eds., Proceedings of the 2009 Leeds Annual Statistical Research Workshop, University of Leeds, 2009c.Google Scholar
Bookstein, F. L., and Kowell, A.. Bringing morphometrics into the fetal alcohol report: Statistical language for the forensic neurologist or psychiatrist. Journal of Psychiatry and Law 38:449474, 2010.CrossRefGoogle Scholar
Bookstein, F. L. Allometry for the twenty-first century. Biological Theory 7:1025, 2013a.CrossRefGoogle Scholar
Bookstein, F. L. Random walk as a null model for geometric morphometrics of fossil series. Paleobiology 39:5274, 2013b.CrossRefGoogle Scholar
Bookstein, F. L., and Ward, P. D.. A modified Procrustes analysis for bilaterally symmetrical outlines, with an application to microevolution in Baculites. Paleobiology 39:214234, 2013.CrossRefGoogle Scholar
Bookstein, F. L. Measuring and Reasoning: Numerical Inference in the Sciences. Cambridge: Cambridge University Press, 2014.CrossRefGoogle Scholar
Bookstein, F. L., and Mitteroecker, P. M.. Comparing covariance matrices by relative eigenanalysis, with applications to organismal biology. Evolutionary Biology 41:336350, 2014.CrossRefGoogle Scholar
Bookstein, F. L. No quantification without qualification, and vice versa. Biological Theory, thematic issue on quality and quantity, doi:10.1007/s13752-015-02213, 10:212227, 2015a.CrossRefGoogle Scholar
Bookstein, F. L. Integration, disintegration, and self-similarity: Characterizing the scales of shape variation in landmark data. Evolutionary Biology, doi 10.1007/s11692–015–9317–8, 42:395426, 2015b.CrossRefGoogle ScholarPubMed
Bookstein, F. L. The relation between geometric morphometrics and functional morphology, as explored by Procrustes interpretation of individual shape measures pertinent to function. Anatomical Record 298:314327, 2015c.CrossRefGoogle ScholarPubMed
Bookstein, F. L. Statistics is founded on entropy, not evolutionary psychology. (Review of Tychomancy by M. Strevens.) Biological Theory, 2015d.Google Scholar
Bookstein, F. L., and Domjanić, J.. The principal components of adult female insole shape align closely with two of its classic indicators. PLOS ONE DOI:10.1371/journal.pone.0133303, August 26, 2015.Google Scholar
Bookstein, F. L. Reconsidering “The inappropriateness of conventional cephalo-metrics.” The American Journal of Orthodontics and Craniofacial Orthopedics 149:784797, 2016a.Google Scholar
Bookstein, F. L. The inappropriate symmetries of multivariate statistical analysis in geometric morphometrics. Evolutionary Biology doi: 10.1007/s11692–016–9382–7, 43:277313, 2016b.CrossRefGoogle Scholar
Bookstein, F. L. A newly noticed formula enforces fundamental limits on geometric morphometric analysis. Evolutionary Biology doi:10.1007/s11692-017-9424-9, 44:524541, 2017a.Google Scholar
Bookstein, F. L. A method of factor analysis for shape coordinates. American Journal of Physical Anthropology doi:10.1002/ajpa.23277, 164:221245, 2017b.CrossRefGoogle ScholarPubMed
Bookstein, F. L. Review of Gilroy and MacPherson, Thieme’s Anatomy Atlas, third edition, Latin nomenclature. Journal of Anatomy doi:10.1111/joa.12684, 231:10191020, 2017c.Google Scholar
Bookstein, F. L., Khambay, B., Kent, J. T., and Mardia, K. V.. Bridging geometric morphometrics to medical anatomy: An example from an experimental study of the human smile. Manuscript in preparation, 2017.Google Scholar
Brennan, S. E. Caricature generator: The dynamic exaggeration of faces by computer. Leonardo 18:170178, 1985.Google Scholar
Bumpus, H. C. The elimination of the unfit as illustrated by the introduced sparrow, Passer domesticus. Biological Lectures of Woods Hole Marine Biological Laboratory, 209–225, 1898.Google Scholar
Calvin, W. H. A Brain for All Seasons: Human Evolution and Abrupt Climate Change. University of Chicago Press, 2002.Google Scholar
Campbell, D. T., and Ross, H. L.. The Connecticut crackdown on speeding: Time-series data in quasi-experimental analysis. Law and Society Review 3:3354, 1968.CrossRefGoogle Scholar
Campbell, D. T., and Stanley, J. C.. Experimental and Quasi-Experimental Designs for Research. Rand-McNally, 1966. Originally published in Gage, N. L., ed., Handbook of Research on Teaching. Rand-McNally, 1963.Google Scholar
Cook, D. L., Neal, M. L., Bookstein, F. L., and Gennari, J. H.. Ontology of physics for biology: Representing physical dependencies as a basis for biological processes. Journal of Biomedical Semantics 4:41, 2013.CrossRefGoogle ScholarPubMed
Cronbach, L. J. The Dependability of Behavioral Measurements: Theory of Generalizability for Scores and Profiles. New York: Wiley, 1972.Google Scholar
Daumier, H. Masques de 1831. La Caricature (Paris), March 8, 1832.Google Scholar
Delattre, A. and Fenart, R. L’hominisation du crâne: étudiée par la méthode vestibulaire. Éditions du Centre national de la recherche scientifique, 1960.Google Scholar
Desimini, J., and Waldheim, C.. Cartographic Grounds: Projecting the Landscape Imaginary. New York: Princeton Architectural Press, 2016.Google Scholar
DeWitte, S. N. Mortality risk and survival in the aftermath of the medieval Black Death. PLOS ONE 9:e96513, 2014.CrossRefGoogle ScholarPubMed
Diaconis, P., Holmes, S., and Montgomery, R.. Dynamical bias in the coin toss. SIAM Review 49:211235, 2007.CrossRefGoogle Scholar
Domjanić, J., Fieder, M., Seidler, H., and Mitteroecker, P. M.. Geometric morphometric footprint analysis of young women. Journal of Foot and Ankle Research 6:2734, 2013.Google Scholar
Draper, N. R., and Smith, H.. Applied Regression Analysis, 3rd ed. New York: Wiley-Interscience, 1998.Google Scholar
Dryden, I. V., and Mardia, K. V.. Statistical Shape Analysis. New York: Wiley, 1998. Second edition, 2016.Google Scholar
Dürer, A. Vier Bücher von menschlicher Proportion. 1528.Google Scholar
Eckart, C., and Young, G.. The approximation of one matrix by another of lower rank. Psychometrika 1:211218, 1936.Google Scholar
Edwards, A. W. F. Likelihood. Baltimore: Johns Hopkins University Press, 1992.Google Scholar
Edwards, W., Lindman, H., and Savage, L. J.. Bayesian statistical inference for psychological research. Psychological Review 70:193242, 1963. (This essay is reprinted in the collected essays of Jimmie Savage, in Volume 1 of S. Kotz and N. L. Johnson, eds., Breakthroughs in Statistics [Springer, 1993], and elsewhere.)CrossRefGoogle Scholar
Einstein, A. [The three immortal papers from Annalen der Physik, 1905.] “On a Heuristic Viewpoint Concerning the Production and Transformation of Light” [the photoelectric effect], June 9. “On the Motion of Small Particles Suspended in a Stationary Liquid, as Required by the Molecular Kinetic Theory of Heat” [Brownian motion], July 18. “On the Electrodynamics of Moving Bodies” [special relativity theory], September 26.Google Scholar
Elsasser, W. M. The Chief Abstractions of Biology. Amsterdam: North-Holland Publishing Co., 1975.Google Scholar
Elsasser, W. M. Reflections on a Theory of Organisms. Cambridge, MA: MIT Press, 1998.CrossRefGoogle Scholar
Farkas, L. G. Anthropometry of the Head and Face. New York: Raven Press, 1994.Google Scholar
Feller, W. An Introduction to Probability Theory and Its Applications, Volume 1, second edition. New York: John Wiley and Sons, 1957.Google Scholar
Felsenstein, J. Inferring Phylogenies. Sunderland, MA: Sinauer Associates, 2004.Google Scholar
Felsenstein, J., and Bookstein, F. L.. Morphometrics on phylogenies. Manuscript in preparation, 2018.Google Scholar
Finch, C. E. The Biology of Human Longevity: Inflammation, Nutrition, and Aging in the Evolution of Lifespans. New York: Academic Press, 2007.Google Scholar
Fisher, R. A. Frequency distribution of the values of the correlation coefficient in samples from an indefinitely large population. Biometrika 10: 507521, 1915.Google Scholar
Fix, E. Distributions which lead to linear regressions. In Neyman, J., ed., Proceedings of the Berkeley Symposium on Mathematical Statistics and Probability 1949, pp. 79–91.Google Scholar
Flury, B. Common Principal Components and Related Multivariate Models. New York: Wiley, 1988.Google Scholar
Fog, D. The geometrical method in the theory of sampling. Biometrika 35: 4654, 1948.Google Scholar
Fornell, C., and Bookstein, F. L.. Two structural equation models: LISREL and PLS applied to market data. Journal of Marketing Research 19:440452, 1982.CrossRefGoogle Scholar
Freedman, D. A. Statistical models and shoe leather. Sociological Methodology 21:291313, 1991.Google Scholar
Freedman, D. A. Statistical Models: Theory and Practice, second edition. Cambridge: Cambridge University Press, 2009.CrossRefGoogle Scholar
Freedman, D. A., and Zeisel, H.. From mouse to man. Statistical Science 3:356, 1988.CrossRefGoogle Scholar
Galton, F. Hereditary Genius: An Inquiry into its Laws and Consequences. London: Macmillan, 1869.CrossRefGoogle Scholar
Galton, F. [Letter to George Darwin, 1877.] In Pearson, K., The Life, Letters, and Labours of Francis Galton. Cambridge: Cambridge University Press, 1930, III:465466.Google Scholar
Galton, F. Natural Inheritance. London: Macmillan, 1889.Google Scholar
Galton, F. Classification of portraits. Nature 76:617618, 1907.Google Scholar
Gerard, R. W., ed. Concepts of Biology. Publication 560. National Academy of Sciences, 1958.Google Scholar
Ghosh, M., and Sinha, B. K.. A simple derivation of the Wishart distribution. The American Statistician 56(2):100101, 2002.Google Scholar
Glaeser, G. Geometry and Its Applications in Arts, Nature and Technology. Vienna: Springer, 2012.Google Scholar
Gleick, J. The Information: A History, a Theory, a Flood. New York: Pantheon, 2011.Google Scholar
Gorjanoviċ-Kramberger, K. Der diluviale Mensch von Krapina in Kroatien: ein Beitrag zur Paläoanthropologie. Wiesbaden: Kreidel’s Verlag, 1906.Google Scholar
Gower, J. C. Some distance properties of latent root and vector methods used in multivariate analysis. Biometrika 53:325338, 1966.Google Scholar
Gower, J. C., and Dijksterhuis, G. B.. Procrustes Problems. Oxford: Oxford University Press, 2004.Google Scholar
Gower, J. C., and Hand, D. J.. Biplots. London: Chapman and Hall, 1995.Google Scholar
Gunz, P. M., Mitteroecker, P. M., Neubauer, S., Weber, G. W., and Bookstein, F. L.. Principles for the virtual reconstruction of hominin crania. Journal of Human Evolution 57:4862, 2009.Google Scholar
Gunz, P., Neubauer, S., Maureille, B., and Hublin, J.-J.. Brain development after birth differs between Neanderthals and modern humans. Current Biology 20:R921– R922, 2010.Google Scholar
Hackshaw, A. K., Law, M. R., and Law, N. J.. The accumulated evidence on lung cancer and environmental tobacco smoke. British Medical Journal 315:980988, 1997.CrossRefGoogle ScholarPubMed
Hallgrimsson, B. S. “Morphometrics and the middle-out approach to complex traits.” Rohlf Award Lecture, http://www.youtube.com/watch?v=kwo9QnJfwn0, October 28, 2015.Google Scholar
Harrison, C. R., and Robinette, K. M.. CAESAR: Summary statistics for the adult population (ages 18–65) of the United States of America. United States Air Force Research Laboratory, Wright-Patterson Air Force Base, 2002.Google Scholar
Harvey, P. H., and Krebs, J. R.. Comparing brains. Science 249:140146, 1990.Google Scholar
Hastie, T., Tibshirani, R., and Friedman, J.. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, second edition. New York: Springer, 2009.Google Scholar
Hellung-Larsen, P., and Andersen, A. P.. Cell volume and dry weight of cultured Tetrahymena. Journal of Cell Science 92:319324, 1989.Google Scholar
Herculano-Houzel, S. The Human Advantage. Cambridge, MA: MIT Press, 2016.Google Scholar
Herculano-Houzel, S., Catania, K., Manger, P. R., and Kaas, J. H.. Mammalian brains are made of these: A dataset of the numbers and densities of neuronal and nonneuronal cells in the brains of glires, primates, scandentia, eulipotyphlans, afrotherians and artiodactyls, and their relationship with body mass. Brain, Behavior and Evolution 86:145163, 2015.Google Scholar
Hinchliff, C. E., and 21 others. Synthesis of phylogeny and taxonomy into a comprehensive tree of life. PNAS 112:1276412769, 2015.Google Scholar
Hogben, L. Chance and Choice by Cardpack and Chessboard. New York: Chanticleer Press, 1950.Google Scholar
Hogben, L. Statistical Theory: The Relationship of Probability, Credibility, and Error. New York: W. W. Norton, 1957.Google Scholar
Huxley, J. Patterns of Relative Growrth. New York: Dial Press, 1932.Google Scholar
Jackson, J. E. A User’s Guide to Principal Components. New York: Wiley-Interscience, 1991.Google Scholar
James, W. The Varieties of Religious Experience. London: Longmans Green & Co., 1902.Google Scholar
Jardine, N. The observational and theoretical components of homology: A study based on the morphology of the dermal skull-roofs of rhipistidian fishes. Biological Journal of the Linnaean Society 1:327361, 1969.Google Scholar
Jaynes, E. T., and Bretthorst, G. L.. Probability Theory: The Logic of Science. Cambridge: Cambridge University Press, 2003.Google Scholar
Jerison, H. J. Paleoneurology and the evolution of mind. Scientific American 234(1): 90101, 1976.CrossRefGoogle ScholarPubMed
Kaiser, H. F. The varimax criterion for analytic rotation in factor analysis. Psychometrika 23:187200, 1958.Google Scholar
Kampourakis, K. Understanding Evolution. Cambridge: Cambridge University Press, 2014.Google Scholar
Keay, J. The Great Arc: The Dramatic Tale of How India Was Mapped and Everest Was Named. New York: HarperCollins, 2000.Google Scholar
Kendall, D. G. Shape manifolds, Procrustean metrics and complex projective spaces. Bulletin of the London Mathematical Society 16:81121, 1984.CrossRefGoogle Scholar
Kendall, M. S. Comment on Hotelling, H., “New light on the correlation coefficient and its transforms.” Journal of the Royal Statistical Society, Series B, 15:225226, 1953.Google Scholar
Koch, G. S., and Link, R. F.. Statistical Analysis of Geological Data. New York: Wiley, 1971.Google Scholar
Krieger, M. H. Doing Physics: How Physicists Take Hold of the World. Bloomington: Indiana University Press, 1992. Second edition, 2012.Google Scholar
Kuhn, T. S. The function of measurement in modern physical science. ISIS 52:161– 193, 1961. Also, pp. 31–63 in Woolf, ed., 1961.Google Scholar
Kullback, S. Information Theory and Statistics. New York: Wiley, 1959.Google Scholar
Lande, R. Quantitative genetic anaysis of multivariate evolution, applied to brain:body size allometry. Evolution 33:402416, 1979.Google Scholar
Law, M. R., Morris, J. K., and Wald, N. J.. Environmental tobacco smoke exposure and ischaemic heart disease: An evaluation of the evidence. British Medical Journal 315:973980, 1997.CrossRefGoogle ScholarPubMed
Li, S. Z., and Jain, A. K., eds. Handbook of Face Recognition, 2nd edition. London: Springer, 2011.CrossRefGoogle Scholar
Lieberson, S. Making It Count: The Improvement of Social Research and Theory. Berkeley: University of California Press, 1985.Google Scholar
Lord, F. M., and Novick, M. R.. Statistical Theories of Mental Test Scores. Reading, MA: Addison-Wesley, 1968.Google Scholar
Lukacs, E. Characterization of populations by properties of suitable statistics. In Neyman, J., ed., Proceedings of the Third Berkeley Symposium on Mathematical Statistics and Probability, 1956, pp. II:195–214.Google Scholar
Mandelbrot, B. B. The Fractalist. New York: Pantheon, 2013.Google Scholar
Marcus, L. F. Traditional morphometrics. In Rohlf and Bookstein, eds., 1990, pp. 77–122.Google Scholar
Marcus, L. F., Corti, M., Loy, A., Naylor, G. J. P., and Slice, D. E., eds. Advances in Morphometrics. New York: Springer, 1996.Google Scholar
Marcus, L. F., Hingst-Zaher, E., and Zaher, H.. Application of landmark morphometrics to skulls representing the orders of living mammals. Hystrix 11:2747, 2000.Google Scholar
Mardia, K. V., Bookstein, F. L., and Kent, J. T.. Alcohol, babies, and the death penalty: Saving lives by analysing the shape of the brain. Significance 10(2):1216, 2013.Google Scholar
Mardia, K. V., Bookstein, F. L., and Moreton, I. J.. Statistical assessment of bilateral symmetry of shapes. Biometrika 87:285300, 2000.CrossRefGoogle Scholar
Mardia, K. V., Bookstein, F. L., Kent, J. T., and Meyer, C. R.. Intrinsic random fields and image deformations. Journal of Mathematical Imaging and Vision 26:5971, 2006.Google Scholar
Mardia, K. V., Kent, J. T., and Bibby, J.. Multivariate Analysis. New York: Wiley, 1979.Google Scholar
Mardia, K. V., and Marshall, R. J.. Maximum likelihood estimation of models for residual covariance in spatial regression. Biometrika 71: 135146, 1984.Google Scholar
Martin, R. Lehrbuch der Anthropologie in systematischer Darstellung. Jena: Gustav Fischer, 1914. 2nd ed., three volumes, 1928.Google Scholar
Martin, R. D. Relative brain size and basal metabolic rate in terrestrial vertebrates. Nature 293:5760, 1981.Google Scholar
Masoro, E. J., and Austad, S. N., eds. Handbook of the Biology of Aging, 7th edition. New York: Academic Press, 2010.Google Scholar
Medawar, P. B. The shape of the human being as a function of time. Proc. Royal Society of London B 132:133141, 1944.Google Scholar
Medawar, P. B. Postscript, . In Thompson, R. D’A., D’Arcy Wentworth Thompson, Oxford: Oxford University Press, 1958.Google Scholar
Millikan, R. A. A direct photoelectric determination of Plancks “h.American Journal of Physics 7:355390, 1916.Google Scholar
Mitteroecker, P. M., and Bookstein, F. L.. The ontogenetic trajectory of the phenotypic covariance matrix, with examples from craniofacial shape in rats and humans. Evolution 63:727737, 2009.Google Scholar
Mitteroecker, P. M., and Bookstein, F. L.. Linear discrimination, ordination, and the visualization of selection gradients in modern morphometrics. Evolutionary Biology 38:100114, 2011.CrossRefGoogle Scholar
Mitteroecker, P. M., and Gunz, P.. Advances in geometric morphometrics. Evolutionary Biology 36:235247, 2009.Google Scholar
Mitteroecker, P., Gunz, P., Weber, G., and Bookstein, F. L.. Regional dissociated heterochrony in multivariate analysis. Annals of Anatomy 186:463470, 2004.Google Scholar
Mosimann, J. E. Size allometry: Size and shape variables with characterizations of the log-normal and generalized gamma distributions. Journal of the American Statistical Association 65:930945, 1970.Google Scholar
Moss, M. L., Skalak, R., Shinozuka, M., Patel, H., Moss-Salentijn, L., Vilmann, H., and Mehta, P.. Statistical testing of an allometric centered model of craniofacial growth. American Journal of Orthodontics 83: 518, 1983.Google Scholar
Mosteller, F. Nonsampling errors. In Sills, D. L., ed., International Encyclopedia of the Social Sciences. New York: Macmillan and the Free Press, 1968, III:113132.Google Scholar
Mosteller, F., and Tukey, J. W.. Data Analysis and Regression: A Second Course in Statistics. New York: Addison-Wesley, 1977.Google Scholar
Moyers, R. E., and Bookstein, F. L.. The inappropriateness of conventional cephalometrics. American Journal of Orthodontics 75:599618, 1979.Google Scholar
Muirhead, R. J. Aspects of Multivariate Statistical Theory. New York: Wiley, 1982.Google Scholar
Olson, E. C., and Miller, R. L.. Morphological Integration. Chicago: University of Chicago Press, 1958.Google Scholar
Ono, M., Kubick, S., and Abernethey, C. D.. Atlas of the Cerebral Sulci. New York: Thieme, 1990.Google Scholar
Oxnard, C. E. The Order of Man: A Biomathematical Anatomy of the Primates. New Haven, CT: Yale University Press, 1984.Google Scholar
Oxnard, C., and OHiggins, P.. Biology clearly needs morphometrics. Does morphometrics need biology? Biological Theory 4:8497, 2009.Google Scholar
Pakkenberg, B., and Gunderson, H. J. G.. Neocortical neuron number in humans: Effect of sex and age. Journal of Comparative Neurology 384:312320, 1997.Google Scholar
Palmer, A. R., and Strobeck, C.. Fluctuating asymmetry: Measurement, analysis, patterns. Annual Reviews of Ecology and Systematics 17:391421, 1986.Google Scholar
Paulos, J. A. A Numerate Life: A Mathematician Explores the Vagaries of Life, His Own and Probably Yours. Amherst, NY: Prometheus Books, 2015.Google Scholar
Pearson, K. The Grammar of Science. London: Walter Scott, 1892. 2nd ed., London: Adam and Charles Black, 1900. 3rd ed., London: Adam and Charles Black, 1911.CrossRefGoogle Scholar
Pearson, K. On lines and planes of closest fit to systems of points in space. Philosophical Magazine Series 6, 2:559572, 1901.Google Scholar
Pearson, K. On the inheritance of the mental and moral characters in man, and its comparison with the inheritance of the physical characters. Journal of the Anthropological Institute of Great Britain and Ireland 33:179237, 1903.Google Scholar
Pearson, K. Walter Frank Raphael Weldon, 1860–1906. Biometrika 5:152, 1906.Google Scholar
Pearson, K., and Filon, L. N. G.. Mathematical contributions to the theory of evolution. IV. On the probable errors of frequency constants and on the influence of random selection on variation and correlation. Philosophical Transactions of the Royal Society of London A 191:229311, 1898.Google Scholar
Pearson, K., and Lee, A.. On the laws of inheritance in man. I: Inheritance of physical characters. Biometrika 2:357462, 1903.Google Scholar
Perrin, J. Atoms, 2nd English edition, revised. London: Constable, 1923.Google Scholar
Peters, R. H. The Ecological Implications of Body Size. Cambridge: Cambridge University Press, 1983.Google Scholar
Platt, J. R. Strong inference. Science 146:347353, 1964.Google Scholar
Pólya, G. Mathematics and Plausible Reasoning, two volumes. Princeton, NJ: Princeton University Press, 1954.Google Scholar
Puget, A., Mejino, J. L. V., Jr., Detwiler, L. T., Franklin, J. D., and Brinkley, J. F.. Spatial-symbolic query engine in anatomy. Methods of Information in Medicine 51:463– 478, 2012.Google Scholar
Ramsay, J., and Silverman, B. W.. Functional Data Analysis, second edition. New York: Springer, 2010.Google Scholar
Rao, C. R. Linear Statistical Inference and Its Applications, second edition. New York: John Wiley & Sons, 1973.Google Scholar
Rentgen, S. Information Graphics. Cologne: Taschen, 2012.Google Scholar
Reyment, R. A. Multidimensional Palaeobiology. Oxford: Pergamon, 1991.Google Scholar
Reyment, R. A., Blackith, R. E., and Campbell, N.. Multivariate Morphometrics, second edition. New York: Academic Press, 1984.Google Scholar
Reyment, R. A., and Jöreskog, K. H.. Applied Factor Analysis in the Natural Sciences. Cambridge: Cambridge University Press, 1993.Google Scholar
Riggs, D. S. The Mathematical Approach to Physiological Problems: A Critical Primer. Cambridge, MA: MIT Press, 1963.Google Scholar
Riolo, M. L., Moyers, R. E., McNamara, J. A. Jr., and Hunter, W. S.. An Atlas of Craniofacial Growth. Craniofacial Monograph 2, Center for Human Growth and Development, University of Michigan, 1974.Google Scholar
Robinette, K. M., Daanen, H., and Paquet, E.. The CAESAR project: A 3-D surface anthropometry survey. In Proceedings of the Second International Conference on 3-D Digital Imaging and Modeling, IEEE, 1999.Google Scholar
Rohlf, F. J. On the use of shape spaces to compare morphometric methods. Hystrix, 11:925, 2000a.Google Scholar
Rohlf, F. J. Statistical power comparisons among alternative morphometric methods. American Journal of Physical Anthropology 111:463478, 2000b.Google Scholar
Rohlf, F. J., and Bookstein, F. L., eds. Proceedings of the Michigan Morphometrics Workshop. Ann Arbor: University of Michigan Museums, 1990.Google Scholar
Rohlf, F. J., and Slice, D. E.. Methods for comparison of sets of landmarks. Systematic Zoology 39:4059, 1990.Google Scholar
Rohlf, F. J., and Sokal, R. R.. Biometry, 4th edition. New York: W. H. Freeman, 2012.Google Scholar
Ross, A. A., Nandakumar, K., and Jain, A. K., eds. Handbook of Multibiometrics. Boston, MA: Springer, 2006.Google Scholar
Rosse, C. The challenges of representing anatomical spatial relations. Methods of Information in Medicine 51:457462, 2012.Google ScholarPubMed
Rosse, C., and Mejino, J. L. V., Jr. A reference ontology for biomedical informatics: The Foundational Model of Anatomy. Journal of Biomedical Informatics 36:478500, 2001.Google Scholar
Roth, G., and Dicke, U.. Evolution of the brain and intelligence in primates. Pp. 413430 in Hofman, M. A. and Falk, D., eds. Progress in Brain Research, vol. 195: Evolution of the Primate Brain: From Neuron to Behavior. Elsevier, 2012.Google Scholar
Schäfer, K., Lauc, T., Mitteroecker, P, Gunz, P., and Bookstein, F. L.. Dental arch asymmetry in an isolated Adriatic community. American Journal of Physical Anthropology 129:132142, 2006.Google Scholar
Schmidt-Nielsen, K. Scaling: Why Is Animal Size So Important? Cambridge: Cambridge Univesrity Press, 1984.Google Scholar
Schoenemann, P. T. An MRI Study of the Relationship Between Human Neuroanatomy and Behavioral Ability. PhD dissertation, University of California at Berkeley, 1997.Google Scholar
Seber, G. A. F., and Wild, C. J.. Nonlinear Regression. New York: Wiley-Interscience, 2003.Google Scholar
Secher, N.J., Djursing, H., Hansen, P. K., Lestrup, C., Eriksen, P. S., Thomsen, B. L., and Keiding, N.. Estimation of fetal weight in the third trimester by ultrasound. European Journal of Obstetrics & Gynecology and Reproductive Biology 24:111, 1987.Google Scholar
Small, C. The Statistical Theory of Shape. New York: Springer 1996.Google Scholar
Sneath, P. H. A. Trend-surface analysis of transformation grids. Journal of Zoology 151:65122, 1967.Google Scholar
Sokal, R. R., and Sneath, P. H. A.. Principles of Numerical Taxonomy. San Francisco: W. H. Freeman Co., 1965.Google Scholar
Stigler, S. M. The History of Statistics: The Measurement of Uncertainty before 1900. Cambridge, MA: Harvard University Press, 1986.Google Scholar
Stone, M. An asymptotic equivalence of choice of model by cross-validation and Akaikes criterion. Journal of the Royal Statistical Society B39:4447, 1977.Google Scholar
Streissguth, A. P., Bookstein, F. L., Barr, H. M., Sampson, P. D., and Young, J. K.. Risk factors for adverse life outcomes in Fetal Alcohol Syndrome and Fetal Alcohol effects. Journal of Developmental and Behavioral Pediatrics 25:228238, 2004.Google Scholar
Strevens, M. Tychomancy: Inferring Probability from Causal Structure. Cambridge, MA: Harvard University Press, 2013.Google Scholar
Stuart, A., and Ord, K.. Kendall’s Advanced Theory of Statistics. Volume 1, Distribution Theory. 1994 edition. London: Griffin.Google Scholar
Taigman, Y., Yang, M., Ranzato, M’A., and Wolf, L.. DeepFace: Closing the gap to human-level performance in face verification. Pp. 17011708 in 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2014.Google Scholar
Taleb, N. N. The Black Swan. New York: Random House, 2007.Google Scholar
Tanner, J. M., and Davies, P. S. W.. Clinical longitudinal standards for height and height velocity for North American children. Journal of Pediatrics 107:317329, 1985.Google Scholar
Federative International Programme on Anatomical Terminologies. Terminologia Anatomica: International Anatomical Terminology. Stuttgart: Thieme, 1998. Second edition, 2011.Google Scholar
Thompson, D’A. W. On Growth and Form. Cambridge: Cambridge University Press, 1917. Second, enlarged edition, 1942. Abridged edition (J. T. Bonner, ed.), 1961.Google Scholar
Torgerson, W. S. Theory and Methods of Scaling. New York: Wiley, 1958.Google Scholar
Tuddenham, R. D., and Snyder, M. M.. Physical growth of California boys and girls from birth to eighteen years. University of California Publications in Child Development 1:183228, 1954.Google Scholar
Wahba, G. Spline Models for Observational Data. Philadelphia: SIAM, 1990.Google Scholar
Weber, G. W., and Bookstein, F. L.. Virtual Anthropology: A Guide to a New Interdisciplinary Field. Berlin: Springer Verlag, 2011.Google Scholar
Weiner, J. The Beak of the Finch. New York: Vintage, 1995.Google Scholar
Weisberg, S. Applied Linear Regression, third edition. New York: John Wiley & Sons, 2005.Google Scholar
Weiss, P. A. [Comments.] In Gerard, 1958, p. 140.Google Scholar
West, G. Scale. New York: Penguin Press, 2017.Google Scholar
West, G. B., Brown, J. H., and Enquist, B. J.. A general model for the origin of allometric scaling laws in biology. Science 276:122126, 1997.Google Scholar
Whittaker, E. The modern approach to Descartes’ problem: The relation of the mathematical and physical sciences to philosophy. The Herbert Spencer Lecture in the University of Oxford. London: Thomas Nelson, 1948.Google Scholar
Wigner, E. The unreasonable effectiveness of mathematics in the natural sciences. Communications in Pure and Applied Mathematics 13:114, 1960.Google Scholar
Williams, R. J. Biochemical Individuality: The Basis for the Genetotrophic Concept. New York: John Wiley and Sons, 1956.Google Scholar
Wilson, E. B. An Introduction to Scientific Research. New York: McGraw-Hill, 1952.Google Scholar
Wilson, E. O. Consilience: The Unity of Knowledge. New York: Knopf, 1998.Google Scholar
Wishart, J. The generalized product moment distribution in samples from a normal multivariate population. Biometrika 290A:3252, 1928.Google Scholar
Wright, S. General, group, and special size factors. Genetics 17:603619, 1932.Google Scholar
Wright, S. Evolution and the Genetics of Populations. Volume 1, Genetic and Biometric Foundations. Chicago: University of Chicago Press, 1968.Google Scholar
Yablokov, A. V. Variability of Mammals. Washington, DC: Amerind, Ltd., for the Smithsonian Institution and the National Science Foundation, 1974.Google Scholar
Zhang, A., Xie, Q., and Srivastava, A.. Elastic registration and shape analysis of functional objects. Pp. 218235 in Dryden, I. L. and Kent, J. T., eds., Geometry-Driven Statistics. Chichester: Wiley, 2015.Google Scholar
Ziman, J. Reliable Knowledge. Cambridge: Cambridge University Press, 1978.Google Scholar

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  • References
  • Fred L. Bookstein, University of Washington
  • Book: A Course in Morphometrics for Biologists
  • Online publication: 21 September 2018
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  • Book: A Course in Morphometrics for Biologists
  • Online publication: 21 September 2018
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  • Book: A Course in Morphometrics for Biologists
  • Online publication: 21 September 2018
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