Gotowa bibliografia na temat „Multivariate Ratio”
Utwórz poprawne odniesienie w stylach APA, MLA, Chicago, Harvard i wielu innych
Zobacz listy aktualnych artykułów, książek, rozpraw, streszczeń i innych źródeł naukowych na temat „Multivariate Ratio”.
Przycisk „Dodaj do bibliografii” jest dostępny obok każdej pracy w bibliografii. Użyj go – a my automatycznie utworzymy odniesienie bibliograficzne do wybranej pracy w stylu cytowania, którego potrzebujesz: APA, MLA, Harvard, Chicago, Vancouver itp.
Możesz również pobrać pełny tekst publikacji naukowej w formacie „.pdf” i przeczytać adnotację do pracy online, jeśli odpowiednie parametry są dostępne w metadanych.
Artykuły w czasopismach na temat "Multivariate Ratio"
Eisenberg, Bennett. "The multivariate Gini ratio". Statistics & Probability Letters 96 (styczeń 2015): 292–98. http://dx.doi.org/10.1016/j.spl.2014.10.009.
Pełny tekst źródłaMarchese, Scott, i Guoqing Diao. "Density ratio model for multivariate outcomes". Journal of Multivariate Analysis 154 (luty 2017): 249–61. http://dx.doi.org/10.1016/j.jmva.2016.11.008.
Pełny tekst źródłaKim, Ilmun, i Sangun Park. "Likelihood ratio tests for multivariate normality". Communications in Statistics - Theory and Methods 47, nr 8 (27.09.2017): 1923–34. http://dx.doi.org/10.1080/03610926.2017.1332218.
Pełny tekst źródłaHui, Siu L., i Saul H. Rosenberg. "Multivariate Slope Ratio Assay with Repeated Measurements". Biometrics 41, nr 1 (marzec 1985): 11. http://dx.doi.org/10.2307/2530638.
Pełny tekst źródłaO’ Brien, Peter C. "A multivariate generalization of von neumann's ratio". Communications in Statistics - Theory and Methods 23, nr 1 (styczeń 1994): 239–47. http://dx.doi.org/10.1080/03610929408831250.
Pełny tekst źródłaHeagerty, Patrick J., i Scott L. Zeger. "Multivariate Continuation Ratio Models: Connections and Caveats". Biometrics 56, nr 3 (wrzesień 2000): 719–32. http://dx.doi.org/10.1111/j.0006-341x.2000.00719.x.
Pełny tekst źródłaSchneeberger, Hans, i Karlheinz Fleischer. "The Multivariate Ratio Estimation/Die mehrdimensionale Verhältnisschätzung". Jahrbücher für Nationalökonomie und Statistik 211, nr 5-6 (1.03.1993): 524–38. http://dx.doi.org/10.1515/jbnst-1993-5-614.
Pełny tekst źródłaLim, Johan, Erning Li i Shin-Jae Lee. "Likelihood ratio tests of correlated multivariate samples". Journal of Multivariate Analysis 101, nr 3 (marzec 2010): 541–54. http://dx.doi.org/10.1016/j.jmva.2009.10.011.
Pełny tekst źródłade Carvalho, Miguel, i Anthony C. Davison. "Spectral Density Ratio Models for Multivariate Extremes". Journal of the American Statistical Association 109, nr 506 (3.04.2014): 764–76. http://dx.doi.org/10.1080/01621459.2013.872651.
Pełny tekst źródłaWang, Yashi, i Peng Zhao. "Multivariate likelihood ratio ordering of conditional order statistics". Journal of Systems Science and Complexity 23, nr 6 (grudzień 2010): 1143–52. http://dx.doi.org/10.1007/s11424-010-7269-8.
Pełny tekst źródłaRozprawy doktorskie na temat "Multivariate Ratio"
North, Robert. "Applications of the dependence ratio association measure for multivariate categorical data". Thesis, University of Southampton, 2015. https://eprints.soton.ac.uk/378642/.
Pełny tekst źródłaLiang, Yuli. "Contributions to Estimation and Testing Block Covariance Structures in Multivariate Normal Models". Doctoral thesis, Stockholms universitet, Statistiska institutionen, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-115347.
Pełny tekst źródłaKarawatzki, Roman, Josef Leydold i Klaus Pötzelberger. "Automatic Markov Chain Monte Carlo Procedures for Sampling from Multivariate Distributions". Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 2005. http://epub.wu.ac.at/1400/1/document.pdf.
Pełny tekst źródłaSeries: Research Report Series / Department of Statistics and Mathematics
Sheppard, Therese. "Extending covariance structure analysis for multivariate and functional data". Thesis, University of Manchester, 2010. https://www.research.manchester.ac.uk/portal/en/theses/extending-covariance-structure-analysis-for-multivariate-and-functional-data(e2ad7f12-3783-48cf-b83c-0ca26ef77633).html.
Pełny tekst źródłaWang, Sai. "GLR Control Charts for Monitoring the Mean Vector or the Dispersion of a Multivariate Normal Process". Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/77227.
Pełny tekst źródłaPh. D.
Karawatzki, Roman, i Josef Leydold. "Automatic Markov Chain Monte Carlo Procedures for Sampling from Multivariate Distributions". Department of Statistics and Mathematics, Abt. f. Angewandte Statistik u. Datenverarbeitung, WU Vienna University of Economics and Business, 2005. http://epub.wu.ac.at/294/1/document.pdf.
Pełny tekst źródłaSeries: Preprint Series / Department of Applied Statistics and Data Processing
Bhatia, Krishan. "USE OF NEAR INFRARED SPECTROSCOPY AND MULTIVARIATE CALIBRATION IN PREDICTING THE PROPERTIES OF TISSUE PAPER MADE OF RECYCLED FIBERS AND VIRGIN PULP". Miami University / OhioLINK, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=miami1077768497.
Pełny tekst źródłaYamane, Danilo Ricardo [UNESP]. "Nutrient diagnosis of orange crops applying compositional data analysis and machine learning techniques". Universidade Estadual Paulista (UNESP), 2018. http://hdl.handle.net/11449/180576.
Pełny tekst źródłaApproved for entry into archive by Tatiana Camila Gricio (tatiana.gricio@unesp.br) on 2019-01-28T17:32:17Z (GMT) No. of bitstreams: 1 yamane_dr_dr_jabo.pdf: 2814108 bytes, checksum: f2e102e5809427e8d3d26d0a59971542 (MD5)
Made available in DSpace on 2019-01-28T17:32:17Z (GMT). No. of bitstreams: 1 yamane_dr_dr_jabo.pdf: 2814108 bytes, checksum: f2e102e5809427e8d3d26d0a59971542 (MD5) Previous issue date: 2018-11-29
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
O manejo eficiente de nutrientes é crucial para atingir alta produtividade de frutos. Resultados da análise do tecido são comumente interpretados usando faixas críticas de concentração de nutrientes (CNCR) e Sistema Integrado de Diagnose e Recomendação (DRIS) em culturas de laranja. No entanto, ambos os métodos ignoram as propriedades inerentes à classe dos dados composicionais, não considerando adequadamente as interações de nutrientes e a influência varietal na composição nutricional da planta. Portanto, ferramentas eficazes de modelagem são necessárias para corrigir vieses e incorporar efeitos genéticos na avaliação do estado nutricional. O objetivo deste estudo foi desenvolver uma abordagem diagnóstica precisa para avaliar o estado nutricional de variedades de copa de laranjeira (Citrus sinensis), usando a análise composicional dos dados e algoritmos de inteligência artificial. Foram coletadas 716 amostras foliares de ramos frutíferos em pomares comerciais de laranjeiras não irrigadas (“Valência”, “Hamlin”, “Pera”, “Natal”, “Valencia Americana” e “Westin”) distribuídos pelo estado de São Paulo (Brasil), analisadas as concentrações de N, S, P, K, Ca, Mg, B, Cu, Zn, Mn e Fe, e avaliadas as produções de frutos. Balanços de nutrientes foram computados como relações-log isométricas (ilr). Análises discriminantes dos valores de ilr diferenciaram os perfis de nutrientes das variedades de copa, indicando composições nutricionais específicas. A acurácia diagnóstica dos balanços de nutrientes atingiu 88% com a produtividade de corte correspondente a 60 t ha-1, utilizando-se ilrs e o algoritmo de classificação knn, o que possibilitou o desenvolvimento de padrões nutricionais confiáveis para a obtenção de elevado nível de produtividade de frutos. Os citricultores do estado de São Paulo devem adotar o conceito de balanços de nutrientes, onde grupos de nutrientes estão equilibrados de maneira ideal. Fornecer mais Ca através de calcário ou gesso, reduzir as aplicações de fertilizantes P e K, e aumentar a fertilização de B via solo pode reequilibrar os balanços [Mg | Ca], [Ca, Mg | K], [P | N, S], [K, Ca, Mg | N, S, P] e [B | N, S, P, K, Ca, Mg] em pomares de laranjas com produtividade inferior a 60 t ha-1. O software “CND-Citros” pode auxiliar os citricultores, engenheiros agrônomos e técnicos a diagnosticar o estado nutricional das lavouras de laranja com base no método proposto, utilizando os resultados da análise química das folhas.
Efficient nutrient management is crucial to attain high fruit productivity. Results of tissue analysis are commonly interpreted using critical nutrient concentration ranges (CNCR) and Diagnosis and Recommendation Integrated System (DRIS) on orange crops. Nevertheless, both methods ignore the inherent properties of compositional data class, not accounting adequately for nutrient interactions and varietal influence on plant ionome. Therefore, effective modeling tools are needed to rectify biases and incorporate genetic effects on nutrient composition. The objective of this study was to develop an accurate diagnostic approach to evaluate the nutritional status across orange (Citrus sinensis) canopy varieties using compositional data analysis and machine learning algorithms. We collected 716 foliar samples from fruit-bearing shoots in plots of non-irrigated commercial orange orchards (“Valencia”, “Hamlin”, “Pera”, “Natal”, “Valencia Americana” and “Westin”) distributed across São Paulo state (Brazil), analyzed N, S, P, K, Ca, Mg, B, Cu, Zn, Mn and Fe, and measured fruit yields. Sound nutrient balances were computed as isometric log-ratios (ilr). Discriminant analysis of ilr values differentiated the nutrient profiles of canopy varieties, indicating plant-specific ionomes. Diagnostic accuracy of nutrient balances reached 88% about cutoff yield of 60 Mg ha-1 using ilrs and a k-nearest neighbors classification, allowing the development of reliable nutritional standards at high fruit yield level. Citrus growers from São Paulo state should adopt the concept of yield-limiting nutrient balances, where groups of nutrients are optimally balanced. Supplying more Ca as lime or gypsum materials, reducing the P and K fertilizer applications and enhancing soil B fertilization could re-establish the [Mg | Ca], [Ca, Mg | K], [P | N, S], [K, Ca, Mg | N, S, P] and [B | N, S, P, K, Ca, Mg] balances in orange orchards yielding less than 60 Mg ha-1. The software “CND-Citros” can assist citrus growers, agronomy engineers and technicians to diagnose the nutrient status of orange crops based on the proposed method, using the results of leaf chemical analysis.
Yamane, Danilo Ricardo. "Nutrient diagnosis of orange crops applying compositional data analysis and machine learning techniques /". Jaboticabal, 2018. http://hdl.handle.net/11449/180576.
Pełny tekst źródłaResumo: O manejo eficiente de nutrientes é crucial para atingir alta produtividade de frutos. Resultados da análise do tecido são comumente interpretados usando faixas críticas de concentração de nutrientes (CNCR) e Sistema Integrado de Diagnose e Recomendação (DRIS) em culturas de laranja. No entanto, ambos os métodos ignoram as propriedades inerentes à classe dos dados composicionais, não considerando adequadamente as interações de nutrientes e a influência varietal na composição nutricional da planta. Portanto, ferramentas eficazes de modelagem são necessárias para corrigir vieses e incorporar efeitos genéticos na avaliação do estado nutricional. O objetivo deste estudo foi desenvolver uma abordagem diagnóstica precisa para avaliar o estado nutricional de variedades de copa de laranjeira (Citrus sinensis), usando a análise composicional dos dados e algoritmos de inteligência artificial. Foram coletadas 716 amostras foliares de ramos frutíferos em pomares comerciais de laranjeiras não irrigadas (“Valência”, “Hamlin”, “Pera”, “Natal”, “Valencia Americana” e “Westin”) distribuídos pelo estado de São Paulo (Brasil), analisadas as concentrações de N, S, P, K, Ca, Mg, B, Cu, Zn, Mn e Fe, e avaliadas as produções de frutos. Balanços de nutrientes foram computados como relações-log isométricas (ilr). Análises discriminantes dos valores de ilr diferenciaram os perfis de nutrientes das variedades de copa, indicando composições nutricionais específicas. A acurácia diagnóstica dos balanços de... (Resumo completo, clicar acesso eletrônico abaixo)
Abstract: Efficient nutrient management is crucial to attain high fruit productivity. Results of tissue analysis are commonly interpreted using critical nutrient concentration ranges (CNCR) and Diagnosis and Recommendation Integrated System (DRIS) on orange crops. Nevertheless, both methods ignore the inherent properties of compositional data class, not accounting adequately for nutrient interactions and varietal influence on plant ionome. Therefore, effective modeling tools are needed to rectify biases and incorporate genetic effects on nutrient composition. The objective of this study was to develop an accurate diagnostic approach to evaluate the nutritional status across orange (Citrus sinensis) canopy varieties using compositional data analysis and machine learning algorithms. We collected 716 foliar samples from fruit-bearing shoots in plots of non-irrigated commercial orange orchards (“Valencia”, “Hamlin”, “Pera”, “Natal”, “Valencia Americana” and “Westin”) distributed across São Paulo state (Brazil), analyzed N, S, P, K, Ca, Mg, B, Cu, Zn, Mn and Fe, and measured fruit yields. Sound nutrient balances were computed as isometric log-ratios (ilr). Discriminant analysis of ilr values differentiated the nutrient profiles of canopy varieties, indicating plant-specific ionomes. Diagnostic accuracy of nutrient balances reached 88% about cutoff yield of 60 Mg ha-1 using ilrs and a k-nearest neighbors classification, allowing the development of reliable nutritional standards at high fruit... (Complete abstract click electronic access below)
Doutor
Mahmoud, Mahmoud A. "The Monitoring of Linear Profiles and the Inertial Properties of Control Charts". Diss., Virginia Tech, 2004. http://hdl.handle.net/10919/29544.
Pełny tekst źródłaPh. D.
Książki na temat "Multivariate Ratio"
Takagi, Hirofumi. Program on the conditional maximum likelihood estimate of the common odds ratio and the AIC in the analysis of K 2x2 tables. Tokyo, Japan: Institute of Statistical Mathematics, 1991.
Znajdź pełny tekst źródłaSrivastava, M. S. Saddlepoint method for obtaining tail probability of Wilk's likelihood ratio test. Toronto: University of Toronto, Dept. of Statistics, 1988.
Znajdź pełny tekst źródłaGilmer, Catherine. An examination of UK equities via ratio analysis in a multiple discriminant analysis framework. Dublin: University College Dublin, 1997.
Znajdź pełny tekst źródłaMussen, Hugh. The application of multivariate techniques in the prediction of companies which are liable to become insolvent based onan analysis of management ratios. [s.l: The Author], 1994.
Znajdź pełny tekst źródłaElwood, Mark. Confounding. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199682898.003.0007.
Pełny tekst źródłaLin, Wen-Ying. Robustness of two multivariate tests to variance-covariance heteroscedasticity and nonnormality when total-sample-size-to-variable ratio is small. 1991.
Znajdź pełny tekst źródłaArnold, Barry C., i Carlos A. Coelho. Finite Form Representations for Meijer G and Fox H Functions: Applied to Multivariate Likelihood Ratio Tests Using Mathematica®, MAXIMA and R. Springer International Publishing AG, 2019.
Znajdź pełny tekst źródłaElwood, Mark. Chance variation. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199682898.003.0008.
Pełny tekst źródłaCzęści książek na temat "Multivariate Ratio"
Gupta, A. K., i D. K. Nagar. "Likelihood Ratio Test for Multisample Sphericity". W Advances in Multivariate Statistical Analysis, 111–39. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-017-0653-7_7.
Pełny tekst źródłaClavel, Jose G., Isabel Martínez Conesa i Esther Ortiz Martínez. "Analyzing Foreign Financial Statements: A Dual Scaling Approach to the International Ratio Analysis". W Measurement and Multivariate Analysis, 307–14. Tokyo: Springer Japan, 2002. http://dx.doi.org/10.1007/978-4-431-65955-6_33.
Pełny tekst źródłaFujikoshi, Yasunori, i Vladimir V. Ulyanov. "Likelihood Ratio Tests with Box-Type Moments". W Non-Asymptotic Analysis of Approximations for Multivariate Statistics, 61–71. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-13-2616-5_6.
Pełny tekst źródłaKeziou, Amor. "Multivariate Divergences with Application in Multisample Density Ratio Models". W Lecture Notes in Computer Science, 444–53. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25040-3_48.
Pełny tekst źródłaLai, Tze Leung, i Li Min Zhang. "Nearly optimal generalized sequential likelihood ratio tests in multivariate exponential families". W Institute of Mathematical Statistics Lecture Notes - Monograph Series, 331–46. Hayward, CA: Institute of Mathematical Statistics, 1994. http://dx.doi.org/10.1214/lnms/1215463806.
Pełny tekst źródłaZang, Wanjun, i Jiang Wen. "Analysis of Slurry Ratio of Rotary Digging Pile in Deep Sand Layer". W Lecture Notes in Civil Engineering, 137–49. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1748-8_11.
Pełny tekst źródłaHolmquist, Björn, Anna Sjöström i Sultana Nasrin. "Approximating Noncentral Chi-Squared to the Moments and Distribution of the Likelihood Ratio Statistic for Multinomial Goodness of Fit". W Recent Developments in Multivariate and Random Matrix Analysis, 175–98. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-56773-6_11.
Pełny tekst źródłaHermy, M., i P. Lewi. "Multivariate Ratio Analysis of Wooded Area, Total Area and Population in the European Community". W Responses of Forest Ecosystems to Environmental Changes, 569–70. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-2866-7_62.
Pełny tekst źródłaRyu, Bikei, Koji Yamaguchi, Tatsuya Ishikawa, Fukui Atsushi, Go Matsuoka, Seiichiro Eguchi, Akitsugu Kawashima, Yoshikazu Okada i Takakazu Kawamata. "Maximum Nidus Depth as a Risk Factor of Surgical Morbidity in Eloquent Brain Arteriovenous Malformations". W Acta Neurochirurgica Supplement, 91–100. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63453-7_14.
Pełny tekst źródłaMaccarone, M. C., R. Buccheri i V. Gesù. "“Multivariate Cluster Analysis of Radio Pulsar Data”". W Data Analysis in Astronomy II, 97–107. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4613-2249-8_9.
Pełny tekst źródłaStreszczenia konferencji na temat "Multivariate Ratio"
Ling, Xiao-Liang, Shu-Xin Luo i Ping Li. "Multivariate Laplace transform ratio order with applications". W 2010 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE, 2010. http://dx.doi.org/10.1109/icmlc.2010.5580645.
Pełny tekst źródłaCastillo-Dura´n, Rogelio, Javier Ortiz-Villafuerte, Raymundo Go´mez-Herrera i Gabriel Calleros-Micheland. "Autoregressive Multivariate Analysis of BWR Bistable Flow". W 16th International Conference on Nuclear Engineering. ASMEDC, 2008. http://dx.doi.org/10.1115/icone16-48730.
Pełny tekst źródłaHuang, Jin-Quan, i Jian-Guo Sun. "Multivariable Adaptive Control for Turbojet Engines". W ASME 1993 International Gas Turbine and Aeroengine Congress and Exposition. American Society of Mechanical Engineers, 1993. http://dx.doi.org/10.1115/93-gt-044.
Pełny tekst źródłaXu, Honglun, Jianguo Wu i Tzu-Liang (Bill) Tseng. "An Efficient Method for Online Identification of Steady State for Multivariate System". W ASME 2018 13th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/msec2018-6565.
Pełny tekst źródłaCaesarendra, Wahyu, Jong Myeong Lee, Jung Min Ha i Byeong Keun Choi. "Slew bearing early damage detection based on multivariate state estimation technique and sequential probability ratio test". W 2015 IEEE International Conference on Advanced Intelligent Mechatronics (AIM). IEEE, 2015. http://dx.doi.org/10.1109/aim.2015.7222696.
Pełny tekst źródłaYang, Guangyuan, Xiaolong Li, Bin Li i Zongming Guo. "A new detector of LSB matching steganography based on likelihood ratio test for multivariate Gaussian covers". W 2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA). IEEE, 2015. http://dx.doi.org/10.1109/apsipa.2015.7415374.
Pełny tekst źródłaOkumura, Hiroshi, Tadashi Sugita, Hironori Matsumoto i Nobuo Takeuchi. "NORMALS — A Noise Reduction Method Using Multivariate Analysis Technique for Lidar Echo Signal". W Optical Remote Sensing of the Atmosphere. Washington, D.C.: Optica Publishing Group, 1993. http://dx.doi.org/10.1364/orsa.1993.tud.19.
Pełny tekst źródłaTagliaferri, Francesca, i Narakorn Srinil. "Quantifying Uncertainties in Phenomenological Model of Two-Dimensional VIV Using Multivariate Monte Carlo Simulations". W ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/omae2017-61058.
Pełny tekst źródłaLiu, Lilan, Hongzhao Liu, Ziying Wu, Daning Yuan i Pengfei Li. "Modal Parameter Identification of Time-Varying Systems Using the Time-Varying Multivariate Autoregressive Model". W ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-84118.
Pełny tekst źródłaCoronado, Horacio Pinzón, Andrea Escobar Porto i Marco E. Sanjuan. "Multivariate Control and Override of a Two-Step Homogeneous Base-Catalyzed Transesterification Process". W ASME 2014 8th International Conference on Energy Sustainability collocated with the ASME 2014 12th International Conference on Fuel Cell Science, Engineering and Technology. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/es2014-6694.
Pełny tekst źródłaRaporty organizacyjne na temat "Multivariate Ratio"
Zhang, Hui Jun, Oliver Linton i Seok Young Hong. Multivariate variance ratio statistics. Cemmap, czerwiec 2014. http://dx.doi.org/10.1920/wp.cem.2014.2914.
Pełny tekst źródłaAnderson, T. W., i H. Hsu. Invariant Tests and Likelihood Ratio Tests for Multivariate Elliptically Contoured Distributions. Fort Belvoir, VA: Defense Technical Information Center, czerwiec 1985. http://dx.doi.org/10.21236/ada155844.
Pełny tekst źródłaLinton, Oliver, Seok Young Hong i Hui Jun Zhang. An investigation into multivariate variance ratio statistics and their application to stock market predictability. Institute for Fiscal Studies, marzec 2015. http://dx.doi.org/10.1920/wp.cem.2015.1315.
Pełny tekst źródłaBoyd, Thomas J., i Richard B. Coffin. Isotope Ratio Spectrometry Data Processing Software: Multivariate Statistical Methods for Hydrocarbon Source Identification and Comparison. Fort Belvoir, VA: Defense Technical Information Center, kwiecień 2004. http://dx.doi.org/10.21236/ada422798.
Pełny tekst źródłaHe, Miao, Zhaoqiong Zhu, Min Jiang, Xingxing Liu, Rui Wu i Junjie Zhou. Risk factors for postanesthetic emergence delirium in adults: A systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, styczeń 2022. http://dx.doi.org/10.37766/inplasy2022.1.0021.
Pełny tekst źródłaClavet, Nicholas-James, Mayssun El-Attar i Raquel Fonseca. Replacement rates of public pensions in canada: heterogeneity across socio-economic status. CIRANO, kwiecień 2022. http://dx.doi.org/10.54932/xcoz6579.
Pełny tekst źródłaClavet, Nicholas-James, Mayssun El-Attar i Raquel Fonseca. Replacement rates of public pensions in canada: heterogeneity across socio-economic status. CIRANO, kwiecień 2022. http://dx.doi.org/10.54932/wsrj9253.
Pełny tekst źródłaTangka, Florence K. L., Sujha Subramanian, Madeleine Jones, Patrick Edwards, Sonja Hoover, Tim Flanigan, Jenya Kaganova i in. Young Breast Cancer Survivors: Employment Experience and Financial Well-Being. RTI Press, lipiec 2020. http://dx.doi.org/10.3768/rtipress.2020.rr.0041.2007.
Pełny tekst źródła