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Statistical Interpretation of Species Composition

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  • Billheimer D.
  • Guttorp P.
  • Fagan W.F.

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  • Billheimer D. & Guttorp P. & Fagan W.F., 2001. "Statistical Interpretation of Species Composition," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1205-1214, December.
    • Handle: RePEc:bes:jnlasa:v:96:y:2001:m:december:p:1205-1214
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    Cited by:

    1. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2015. "Dynamic predictive density combinations for large data sets in economics and finance," Working Paper 2015/12, Norges Bank.
    2. Jacob Fiksel & Scott Zeger & Abhirup Datta, 2022. "A transformation‐free linear regression for compositional outcomes and predictors," Biometrics, The International Biometric Society, vol. 78(3), pages 974-987, September.
    3. Yaru Song & Hongyu Zhao & Tao Wang, 2020. "An adaptive independence test for microbiome community data," Biometrics, The International Biometric Society, vol. 76(2), pages 414-426, June.
    4. Menafoglio, Alessandra & Secchi, Piercesare, 2017. "Statistical analysis of complex and spatially dependent data: A review of Object Oriented Spatial Statistics," European Journal of Operational Research, Elsevier, vol. 258(2), pages 401-410.
    5. Duo Jiang & Thomas Sharpton & Yuan Jiang, 2021. "Microbial Interaction Network Estimation via Bias-Corrected Graphical Lasso," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 13(2), pages 329-350, July.
    6. J. Haslett & M. Whiley & S. Bhattacharya & M. Salter‐Townshend & Simon P. Wilson & J. R. M. Allen & B. Huntley & F. J. G. Mitchell, 2006. "Bayesian palaeoclimate reconstruction," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(3), pages 395-438, July.
    7. Antonio Martin Arroyo & Aranzazu de Juan Fernandez, 2020. "Split-then-Combine simplex combination and selection of forecasters," Papers 2012.11935, arXiv.org.
    8. Wang, Huiwen & Liu, Qiang & Mok, Henry M.K. & Fu, Linghui & Tse, Wai Man, 2007. "A hyperspherical transformation forecasting model for compositional data," European Journal of Operational Research, Elsevier, vol. 179(2), pages 459-468, June.
    9. Zhigang Li & Katherine Lee & Margaret R. Karagas & Juliette C. Madan & Anne G. Hoen & A. James O’Malley & Hongzhe Li, 2018. "Conditional Regression Based on a Multivariate Zero-Inflated Logistic-Normal Model for Microbiome Relative Abundance Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 10(3), pages 587-608, December.
    10. Terence Mills, 2010. "Forecasting compositional time series," Quality & Quantity: International Journal of Methodology, Springer, vol. 44(4), pages 673-690, June.
    11. Jiajia Chen & Xiaoqin Zhang & Shengjia Li, 2017. "Multiple linear regression with compositional response and covariates," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(12), pages 2270-2285, September.
    12. Violetta Simonacci & Michele Gallo, 2019. "Detecting Public Social Spending Patterns in Italy Using a Three-Way Relative Variation Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(1), pages 205-219, November.
    13. K. Hron & P. Filzmoser & K. Thompson, 2012. "Linear regression with compositional explanatory variables," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(5), pages 1115-1128, November.
    14. Michele Gallo & Violetta Simonacci & Maria Anna Palma, 2019. "An integrated algorithm for three-way compositional data," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(5), pages 2353-2370, September.
    15. Juan José Egozcue & Vera Pawlowsky-Glahn, 2019. "Compositional data: the sample space and its structure," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(3), pages 599-638, September.
    16. John Mullahy, 2010. "Multivariate Fractional Regression Estimation of Econometric Share Models," NBER Working Papers 16354, National Bureau of Economic Research, Inc.
    17. Johnson, Devin S. & Hoeting, Jennifer A., 2011. "Properties of graphical regression models for multidimensional categorical data," Statistics & Probability Letters, Elsevier, vol. 81(10), pages 1471-1475, October.
    18. Karel Hron & Paula Brito & Peter Filzmoser, 2017. "Exploratory data analysis for interval compositional data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 11(2), pages 223-241, June.
    19. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2019. "Forecast density combinations with dynamic learning for large data sets in economics and finance," Working Paper 2019/7, Norges Bank.
    20. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2020. "A Bayesian Dynamic Compositional Model for Large Density Combinations in Finance," Working Paper series 20-27, Rimini Centre for Economic Analysis.

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