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Relevant bibliographies by topics / Multivariate Ratio

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Academic literature on the topic 'Multivariate Ratio'

Author: Grafiati

Published: 8 September 2023

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Journal articles on the topic "Multivariate Ratio"

1

Eisenberg, Bennett. "The multivariate Gini ratio." Statistics & Probability Letters 96 (January 2015): 292–98. http://dx.doi.org/10.1016/j.spl.2014.10.009.

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Marchese, Scott, and Guoqing Diao. "Density ratio model for multivariate outcomes." Journal of Multivariate Analysis 154 (February 2017): 249–61. http://dx.doi.org/10.1016/j.jmva.2016.11.008.

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Kim, Ilmun, and Sangun Park. "Likelihood ratio tests for multivariate normality." Communications in Statistics - Theory and Methods 47, no. 8 (September 27, 2017): 1923–34. http://dx.doi.org/10.1080/03610926.2017.1332218.

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Hui, Siu L., and Saul H. Rosenberg. "Multivariate Slope Ratio Assay with Repeated Measurements." Biometrics 41, no. 1 (March 1985): 11. http://dx.doi.org/10.2307/2530638.

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O’ Brien, Peter C. "A multivariate generalization of von neumann's ratio." Communications in Statistics - Theory and Methods 23, no. 1 (January 1994): 239–47. http://dx.doi.org/10.1080/03610929408831250.

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Heagerty, Patrick J., and Scott L. Zeger. "Multivariate Continuation Ratio Models: Connections and Caveats." Biometrics 56, no. 3 (September 2000): 719–32. http://dx.doi.org/10.1111/j.0006-341x.2000.00719.x.

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Schneeberger, Hans, and Karlheinz Fleischer. "The Multivariate Ratio Estimation/Die mehrdimensionale Verhältnisschätzung." Jahrbücher für Nationalökonomie und Statistik 211, no. 5-6 (March 1, 1993): 524–38. http://dx.doi.org/10.1515/jbnst-1993-5-614.

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Lim, Johan, Erning Li, and Shin-Jae Lee. "Likelihood ratio tests of correlated multivariate samples." Journal of Multivariate Analysis 101, no. 3 (March 2010): 541–54. http://dx.doi.org/10.1016/j.jmva.2009.10.011.

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de Carvalho, Miguel, and Anthony C. Davison. "Spectral Density Ratio Models for Multivariate Extremes." Journal of the American Statistical Association 109, no. 506 (April 3, 2014): 764–76. http://dx.doi.org/10.1080/01621459.2013.872651.

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Wang, Yashi, and Peng Zhao. "Multivariate likelihood ratio ordering of conditional order statistics." Journal of Systems Science and Complexity 23, no. 6 (December 2010): 1143–52. http://dx.doi.org/10.1007/s11424-010-7269-8.

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Dissertations / Theses on the topic "Multivariate Ratio"

1

North, Robert. "Applications of the dependence ratio association measure for multivariate categorical data." Thesis, University of Southampton, 2015. https://eprints.soton.ac.uk/378642/.

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Liang, 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.

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This thesis concerns inference problems in balanced random effects models with a so-called block circular Toeplitz covariance structure. This class of covariance structures describes the dependency of some specific multivariate two-level data when both compound symmetry and circular symmetry appear simultaneously. We derive two covariance structures under two different invariance restrictions. The obtained covariance structures reflect both circularity and exchangeability present in the data. In particular, estimation in the balanced random effects with block circular covariance matrices is considered. The spectral properties of such patterned covariance matrices are provided. Maximum likelihood estimation is performed through the spectral decomposition of the patterned covariance matrices. Existence of the explicit maximum likelihood estimators is discussed and sufficient conditions for obtaining explicit and unique estimators for the variance-covariance components are derived. Different restricted models are discussed and the corresponding maximum likelihood estimators are presented. This thesis also deals with hypothesis testing of block covariance structures, especially block circular Toeplitz covariance matrices. We consider both so-called external tests and internal tests. In the external tests, various hypotheses about testing block covariance structures, as well as mean structures, are considered, and the internal tests are concerned with testing specific covariance parameters given the block circular Toeplitz structure. Likelihood ratio tests are constructed, and the null distributions of the corresponding test statistics are derived.

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Karawatzki, Roman, Josef Leydold, and 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.

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Generating samples from multivariate distributions efficiently is an important task in Monte Carlo integration and many other stochastic simulation problems. Markov chain Monte Carlo has been shown to be very efficient compared to "conventional methods", especially when many dimensions are involved. In this article we propose a Hit-and-Run sampler in combination with the Ratio-of-Uniforms method. We show that it is well suited for an algorithm to generate points from quite arbitrary distributions, which include all log-concave distributions. The algorithm works automatically in the sense that only the mode (or an approximation of it) and an oracle is required, i.e., a subroutine that returns the value of the density function at any point x. We show that the number of evaluations of the density increases slowly with dimension. An implementation of these algorithms in C is available from the authors. (author's abstract)
Series: Research Report Series / Department of Statistics and Mathematics

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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.

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For multivariate data, when testing homogeneity of covariance matrices arising from two or more groups, Bartlett's (1937) modified likelihood ratio test statistic is appropriate to use under the null hypothesis of equal covariance matrices where the null distribution of the test statistic is based on the restrictive assumption of normality. Zhang and Boos (1992) provide a pooled bootstrap approach when the data cannot be assumed to be normally distributed. We give three alternative bootstrap techniques to testing homogeneity of covariance matrices when it is both inappropriate to pool the data into one single population as in the pooled bootstrap procedure and when the data are not normally distributed. We further show that our alternative bootstrap methodology can be extended to testing Flury's (1988) hierarchy of covariance structure models. Where deviations from normality exist, we show, by simulation, that the normal theory log-likelihood ratio test statistic is less viable compared with our bootstrap methodology. For functional data, Ramsay and Silverman (2005) and Lee et al (2002) together provide four computational techniques for functional principal component analysis (PCA) followed by covariance structure estimation. When the smoothing method for smoothing individual profiles is based on using least squares cubic B-splines or regression splines, we find that the ensuing covariance matrix estimate suffers from loss of dimensionality. We show that ridge regression can be used to resolve this problem, but only for the discretisation and numerical quadrature approaches to estimation, and that choice of a suitable ridge parameter is not arbitrary. We further show the unsuitability of regression splines when deciding on the optimal degree of smoothing to apply to individual profiles. To gain insight into smoothing parameter choice for functional data, we compare kernel and spline approaches to smoothing individual profiles in a nonparametric regression context. Our simulation results justify a kernel approach using a new criterion based on predicted squared error. We also show by simulation that, when taking account of correlation, a kernel approach using a generalized cross validatory type criterion performs well. These data-based methods for selecting the smoothing parameter are illustrated prior to a functional PCA on a real data set.

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Wang, 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.

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In many applications, the quality of process outputs is described by more than one characteristic variable. These quality variables usually follow a multivariate normal (MN) distribution. This dissertation discusses the monitoring of the mean vector and the covariance matrix of MN processes. The first part of this dissertation develops a statistical process control (SPC) chart based on a generalized likelihood ratio (GLR) statistic to monitor the mean vector. The performance of the GLR chart is compared to the performance of the Hotelling Χ² chart, the multivariate exponentially weighted moving average (MEWMA) chart, and a multi-MEWMA combination. Results show that the Hotelling Χ² chart and the MEWMA chart are only effective for a small range of shift sizes in the mean vector, while the GLR chart and some carefully designed multi-MEWMA combinations can give similarly better overall performance in detecting a wide range of shift magnitudes. Unlike most of these other options, the GLR chart does not require specification of tuning parameter values by the user. The GLR chart also has the advantage in process diagnostics: at the time of a signal, estimates of change-point and out-of-control mean vector are immediately available to the user. All these advantages of the GLR chart make it a favorable option for practitioners. For the design of the GLR chart, a series of easy to use equations are provided to users for calculating the control limit to achieve the desired in-control performance. The use of this GLR chart with a variable sampling interval (VSI) scheme has also been evaluated and discussed. The rest of the dissertation considers the problem of monitoring the covariance matrix. Three GLR charts with different covariance matrix estimators have been discussed. Results show that the GLR chart with a multivariate exponentially weighted moving covariance (MEWMC) matrix estimator is slightly better than the existing method for detecting any general changes in the covariance matrix, and the GLR chart with a constrained maximum likelihood estimator (CMLE) gives much better overall performance for detecting a wide range of shift sizes than the best available options for detecting only variance increases.
Ph. D.

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Karawatzki, Roman, and 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.

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Generating samples from multivariate distributions efficiently is an important task in Monte Carlo integration and many other stochastic simulation problems. Markov chain Monte Carlo has been shown to be very efficient compared to "conventional methods", especially when many dimensions are involved. In this article we propose a Hit-and-Run sampler in combination with the Ratio-of-Uniforms method. We show that it is well suited for an algorithm to generate points from quite arbitrary distributions, which include all log-concave distributions. The algorithm works automatically in the sense that only the mode (or an approximation of it) and an oracle is required, i.e., a subroutine that returns the value of the density function at any point x. We show that the number of evaluations of the density increases slowly with dimension. (author's abstract)
Series: Preprint Series / Department of Applied Statistics and Data Processing

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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.

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Yamane, 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.

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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.

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Yamane, Danilo Ricardo. "Nutrient diagnosis of orange crops applying compositional data analysis and machine learning techniques /." Jaboticabal, 2018. http://hdl.handle.net/11449/180576.

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Orientador: Arthur Bernardes Cecílio Filho
Resumo: 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

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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.

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The Phase I analysis of data when the quality of a process or product is characterized by a linear function is studied in this dissertation. It is assumed that each sample collected over time in the historical data set consists of several bivariate observations for which a simple linear regression model is appropriate, a situation common in calibration applications. Using a simulation study, the researcher compares the performance of some of the recommended approaches used to assess the stability of the process. Also in this dissertation, a method based on using indicator variables in a multiple regression model is proposed. This dissertation also proposes a change point approach based on the segmented regression technique for testing the constancy of the regression parameters in a linear profile data set. The performance of the proposed change point method is compared to that of the most effective Phase I linear profile control chart approaches using a simulation study. The advantage of the proposed change point method over the existing methods is greatly improved detection of sustained step changes in the process parameters. Any control chart that combines sample information over time, e.g., the cumulative sum (CUSUM) chart and the exponentially weighted moving average (EWMA) chart, has an ability to detect process changes that varies over time depending on the past data observed. The chart statistics can take values such that some shifts in the parameters of the underlying probability distribution of the quality characteristic are more difficult to detect. This is referred to as the "inertia problem" in the literature. This dissertation shows under realistic assumptions that the worst-case run length performance of control charts becomes as informative as the steady-state performance. Also this study proposes a simple new measure of the inertial properties of control charts, namely the signal resistance. The conclusions of this study support the recommendation that Shewhart limits should be used with EWMA charts, especially when the smoothing parameter is small. This study also shows that some charts proposed by Pignatiello and Runger (1990) and Domangue and Patch (1991) have serious disadvantages with respect to inertial properties.
Ph. D.

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Books on the topic "Multivariate Ratio"

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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.

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Srivastava, M. S. Saddlepoint method for obtaining tail probability of Wilk's likelihood ratio test. Toronto: University of Toronto, Dept. of Statistics, 1988.

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Gilmer, Catherine. An examination of UK equities via ratio analysis in a multiple discriminant analysis framework. Dublin: University College Dublin, 1997.

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Mussen, 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.

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Elwood, Mark. Confounding. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199682898.003.0007.

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This chapter gives the definition of confounding, a central issue in epidemiology and its dependence on two associations, with exposure and with outcome. It explains confounding in trials, cohort and case-control studies, and Simpson’s paradox. It explains the five methods of controlling confounding: restriction, randomisation, stratification, matching and multivariate methods. For randomised trials, the limits of randomisation, residual confounding, pre-stratification, intention-to-treat, management and explanatory trials, pragmatic trials are explained. It shows the Mantel–Haenszel risk ratio or odds ratio, direct and indirect standardisation, and effect modification. Frequency and individual matching, their value and limitations, over matching, confounding by indication, and calculation of matched odds ratio are shown. It explains multivariate methods, including linear, logistic, Poisson, and Cox’s proportionate hazards models, including the relationship between coefficients and odds ratios, dummy variables, conditional methods, and propensity scores.

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Lin, Wen-Ying. Robustness of two multivariate tests to variance-covariance heteroscedasticity and nonnormality when total-sample-size-to-variable ratio is small. 1991.

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Arnold, Barry C., and 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.

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Elwood, Mark. Chance variation. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199682898.003.0008.

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This chapter explains chance variation and statistical tests, including discrete and continuous measures, the concept of significance, one and two sided test, exact tests, precision and confidence limits. It shows tests of differences in proportions and chi-square tests, the Mantel-Haenszel test, and calculation of confidence limits, for simple tables and for stratified data. It covers heterogeneity tests, multiplicative and additive models, ordered exposure variables and tests of trend. It explains statistical tests for matched studies and in multivariate models. Multiple testing, the Bonferroni correction, issues of hypothesis testing and hypothesis generation, and subgroup analyses are discussed. Stopping rules and repeated testing in trials is covered. It explains how to calculate study power and the necessary size of the study. The chapter describes time to event analysis, including survival curves, product-limit and actuarial or life-table methods, and the calculation of confidence limits, relative survival ratios, the log rank test with control for confounding, and multivariate analysis.

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Book chapters on the topic "Multivariate Ratio"

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Gupta, A. K., and D. K. Nagar. "Likelihood Ratio Test for Multisample Sphericity." In Advances in Multivariate Statistical Analysis, 111–39. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-017-0653-7_7.

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Clavel, Jose G., Isabel Martínez Conesa, and Esther Ortiz Martínez. "Analyzing Foreign Financial Statements: A Dual Scaling Approach to the International Ratio Analysis." In Measurement and Multivariate Analysis, 307–14. Tokyo: Springer Japan, 2002. http://dx.doi.org/10.1007/978-4-431-65955-6_33.

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Fujikoshi, Yasunori, and Vladimir V. Ulyanov. "Likelihood Ratio Tests with Box-Type Moments." In 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.

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Keziou, Amor. "Multivariate Divergences with Application in Multisample Density Ratio Models." In Lecture Notes in Computer Science, 444–53. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25040-3_48.

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Lai, Tze Leung, and Li Min Zhang. "Nearly optimal generalized sequential likelihood ratio tests in multivariate exponential families." In 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.

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Zang, Wanjun, and Jiang Wen. "Analysis of Slurry Ratio of Rotary Digging Pile in Deep Sand Layer." In Lecture Notes in Civil Engineering, 137–49. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1748-8_11.

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AbstractSlurry ratio is a crucial link in the construction of bored pile, which directly determines the quality of bored pile. In order to determine the key performance parameters of the slurry required to form piles in the deep sand layer, relying on Huizhou north station engineering, an orthogonal test of slurry proportioning was designed and carried out, and SPSS statistical analysis software was used to carry out bivariate correlation analysis and multivariate stepwise analysis of the test results, combined with the slurry performance index test regression equation and using MATLAB software optimization processing, slurry optimal mix ratio and verify, the research results show that: orthogonal test screening value, software calculation value, test value is not different. Conclusion: The results show that bentonite and CMC have significant influence on slurry indexes, while Na2CO3 and PHP can adjust slurry performance to meet the slurry use standard; the optimal mix ratio is 148 g bentonite, Na2CO3 5.2 g, CMC 3.5 g, PHP 0.05 g; the slurry ratio test analysis and treatment, and the optimization mix ratio is feasible and reasonable, class I pile proportion more than 98% to meet the actual engineering requirements.

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Holmquist, Björn, Anna Sjöström, and Sultana Nasrin. "Approximating Noncentral Chi-Squared to the Moments and Distribution of the Likelihood Ratio Statistic for Multinomial Goodness of Fit." In 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.

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Hermy, M., and P. Lewi. "Multivariate Ratio Analysis of Wooded Area, Total Area and Population in the European Community." In 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.

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Ryu, Bikei, Koji Yamaguchi, Tatsuya Ishikawa, Fukui Atsushi, Go Matsuoka, Seiichiro Eguchi, Akitsugu Kawashima, Yoshikazu Okada, and Takakazu Kawamata. "Maximum Nidus Depth as a Risk Factor of Surgical Morbidity in Eloquent Brain Arteriovenous Malformations." In Acta Neurochirurgica Supplement, 91–100. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63453-7_14.

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AbstractBackground: Eloquent location of a brain arteriovenous malformation (BAVM) is known to increase the surgical risk. Surgical removal of such BAVMs is challenging. Useful indicators for the safe removal of eloquent BAVMs are needed. The aim of this study was to determine the surgical risk factors for these challenging entities.Methods: The authors retrospectively reviewed 29 motor and/or sensory BAVM patients who underwent surgeries. The risk factors for surgical morbidity were analyzed. As a new risk factor, maximum nidus depth, was evaluated.Results: Complete obliteration was achieved in 28 patients (96.6%). Postoperative transient and permanent neurological deteriorations were seen in nine patients (31.0%) and five patients (17.2%), respectively. In univariate analysis, maximum nidus depth (p = 0.0204) and asymptomatic onset (p = 0.0229) were significantly correlated with the total morbidity. In multivariate analysis, only maximum nidus depth was significantly correlated with total morbidity (p = 0.0357; odds ratio, 2.78598; 95% confidence interval, 0.8866–8.7535). The cut-off value for the maximum nidus depth was 36 mm for total morbidity (area under the curve [AUC], 0.7428) and 41 mm for permanent morbidity (AUC, 0.8833). The cutoff value of the maximum nidus size was 30 mm for total morbidity (AUC, 0.5785) and 30 mm for permanent morbidity (AUC, 0.7625). AUC was higher for the maximum nidus depth than it was for the maximum nidus size.Conclusions: Maximum nidus depth was significantly associated with surgical morbidity of eloquent BAVMs. The maximum nidus depth is a novel and a simpler indicator of the risk of surgical morbidity.

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Maccarone, M. C., R. Buccheri, and V. Gesù. "“Multivariate Cluster Analysis of Radio Pulsar Data”." In Data Analysis in Astronomy II, 97–107. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4613-2249-8_9.

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Conference papers on the topic "Multivariate Ratio"

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Ling, Xiao-Liang, Shu-Xin Luo, and Ping Li. "Multivariate Laplace transform ratio order with applications." In 2010 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE, 2010. http://dx.doi.org/10.1109/icmlc.2010.5580645.

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Castillo-Dura´n, Rogelio, Javier Ortiz-Villafuerte, Raymundo Go´mez-Herrera, and Gabriel Calleros-Micheland. "Autoregressive Multivariate Analysis of BWR Bistable Flow." In 16th International Conference on Nuclear Engineering. ASMEDC, 2008. http://dx.doi.org/10.1115/icone16-48730.

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Bi-stable flow patterns can induce flow oscillations possibly leading to power fluctuations. In other cases, bi-stable flow can generate loads on components, so that structural stresses may become a potential cause of failure. This type of flow occurs in BWRs at different operation conditions, so there is no an absolute methodology for detection and prediction of such phenomenon. In this work, a multivariate autoregressive (MAR) analysis is performed to different signals related to a bi-stable flow event that occurred in one of the BWR Units at the Laguna Verde Nuclear Power Plant. The signal analysis was performed with the home-developed NOISE computer program, which, among several other applications, computes the autoregressive coefficients which contain the information of the dynamics of the signal, and that later are used to determine the relative power contribution (RPC) ratio, which in turn allows establishing the influence of the different signals on each other. From the signal analysis, among the important results obtained, it was found that no new frequencies appeared during the event. Also, it was determined through the Relative Power Contribution ratios that the most probable cause of reactor power change was the flow variation in the recirculation flow of loop B. Maximum variations (both above and below) from the initial average reactor power were 0.5%, so the bi-stable flow impact was of no safety concern.

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Huang, Jin-Quan, and Jian-Guo Sun. "Multivariable Adaptive Control for Turbojet Engines." In 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.

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Integrated flight and propulsion control systems will require propulsion systems to reduce in time to accelerate engine and to improve transient performance for a full flight envelope operation. A multivariate model reference adaptive control (MRAC) scheme is proposed in this paper. Acceleration time is reduced by uptrimming engine pressure ratio in some operating conditions and in parts of the flight envelope where excess stall margin and turbine temperature margin exist. The MRAC scheme is obtained by using Liapunov direct method. Simulation studies are performed for a two-spool turbojet engine. The satisfactory transient responses are obtained at different operating points from idle to maximum dry power in flight envelope which shows good robustness for unmodelled dynamics of nonlinear engine. Simulation results also show the good effectiveness of reducing interaction in multivariable system with significant coupling. Using the Multivariable MRAC controller, the engine acceleration time is reduced about 16 percent in comparison with the conventional engine controller.

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Xu, Honglun, Jianguo Wu, and Tzu-Liang (Bill) Tseng. "An Efficient Method for Online Identification of Steady State for Multivariate System." In ASME 2018 13th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/msec2018-6565.

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Most of the existing steady state detection approaches are designed for univariate signals. For multivariate signals, the univariate approach is often applied to each process variable and the system is claimed to be steady once all signals are steady, which is computationally inefficient and also not accurate. The article proposes an efficient online method for multivariate steady state detection. It estimates the covariance matrices using two different approaches, namely, the mean-squared-deviation and mean-squared-successive-difference. To avoid the usage of a moving window, the process means and the two covariance matrices are calculated recursively through exponentially weighted moving average. A likelihood ratio test is developed to compare the difference of the two covariance matrices and to detect the steady state. The intensive numerical studies and real case study show that the proposed method can accurately detect the steady state of a multivariate system.

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Caesarendra, Wahyu, Jong Myeong Lee, Jung Min Ha, and Byeong Keun Choi. "Slew bearing early damage detection based on multivariate state estimation technique and sequential probability ratio test." In 2015 IEEE International Conference on Advanced Intelligent Mechatronics (AIM). IEEE, 2015. http://dx.doi.org/10.1109/aim.2015.7222696.

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Yang, Guangyuan, Xiaolong Li, Bin Li, and Zongming Guo. "A new detector of LSB matching steganography based on likelihood ratio test for multivariate Gaussian covers." In 2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA). IEEE, 2015. http://dx.doi.org/10.1109/apsipa.2015.7415374.

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Okumura, Hiroshi, Tadashi Sugita, Hironori Matsumoto, and Nobuo Takeuchi. "NORMALS — A Noise Reduction Method Using Multivariate Analysis Technique for Lidar Echo Signal." In Optical Remote Sensing of the Atmosphere. Washington, D.C.: Optica Publishing Group, 1993. http://dx.doi.org/10.1364/orsa.1993.tud.19.

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Portable lidar system is a powerful tool for monitoring air pollution, stratospheric and boundary layer, plume dispersion, visibility, and studying atmospheric structure and cloud physics. However, the signal-to-noise (S / N) ratio of each echo datum which is acquired with such portable lidar systems is not so high because of its low lasing power in comparison with large scale lidar systems.

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Tagliaferri, Francesca, and Narakorn Srinil. "Quantifying Uncertainties in Phenomenological Model of Two-Dimensional VIV Using Multivariate Monte Carlo Simulations." In 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.

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Phenomenological modelling based on the use of coupled wake-cylinder oscillators has been implemented for several decades for vortex-induced vibration (VIV) response predictions of rigid circular cylinders and long flexible risers. Although such models can capture several VIV nonlinear phenomena, they still rely on empirical coefficients and parameters with some levels of uncertainties associated with fluid-structure interactions. Most of these are due to the variation in experimental test conditions giving rise to different benchmarking test data in the literature. A very few studies have quantified such model uncertainties. To gain an insight into the relative contributions of these coefficients, this paper presents a sensitivity study based on a multivariate Sobol-Monte Carlo approach for a two-dimensional nonlinear coupled wake-cylinder oscillator model simulating combined cross-flow/in-line VIV. A preliminary investigation is carried out to identify the relative contribution to the model uncertainty of the geometrical, empirical wake and wake-cylinder coupling coefficients. The effect of Reynolds number (Re) in the subcritical flow regime is also taken into account through a lift, drag, Strouhal and wake coefficient depending on calibration with experimental data. A key challenge is the identification of suitable probability distribution function to model the scattering experimental datasets. A combination of Gaussian and uniform distributions are calibrated. Parametric studies based on the combined Sobol-Monte Carlo simulations reveal the uncertainties due to the coupling of empirical coefficients and system parameters governing the two-dimensional lock-in and combined cross-flow/in-line VIV responses. The relative importance of the selected wake coefficients and geometric parameters appears to be strongly dependent on the system mass ratio as well as Re influencing the hydrodynamic properties including the lift and drag coefficients, the Strouhal number and stall parameter. For the cylinder with a lower mass ratio, greater uncertainties are found within the considered sub-critical Re range for both cross-flow/in-line VIV. This remark should also be recognized in the phenomenological VIV modelling of long flexible risers in offshore applications.

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Liu, Lilan, Hongzhao Liu, Ziying Wu, Daning Yuan, and Pengfei Li. "Modal Parameter Identification of Time-Varying Systems Using the Time-Varying Multivariate Autoregressive Model." In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-84118.

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A new time-varying multivariate autoregressive (TVMAR) model method for modal parameter identification of linear time-varying (TV) systems with multi-output is introduced. Besides, a modified recursive least square method based on the traditional one is presented to determine the coefficient matrices of the TVMAR model. In the proposed method, multi-dimensional nonstationary response signals of the vibrating system can be processed simultaneously. Not only the TV modal frequency and damping ratio of the system, but also the changing behavior of the mode shape in the course of vibration are identified by the proposed procedure. Numerical simulations, in which a three-degree-of-freedom system with TV stiffness is respectively subjected to impulse excitation and white noise excitation, are presented. The validity and accuracy of the method are demonstrated by the good simulation results.

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Coronado, Horacio Pinzón, Andrea Escobar Porto, and Marco E. Sanjuan. "Multivariate Control and Override of a Two-Step Homogeneous Base-Catalyzed Transesterification Process." In 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.

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The most common technology used in biodiesel production is the transesterification of vegetable oils and animal fats. Transesterification (also called alcoholysis) is the reaction of fat oil with an alcohol to form esters and glycerol, in presence of catalyst to improve the reaction rate and yield. Although process industry has established long ago that continuous processes are more cost-effective than batch processing, there is still a substantial number of batch processing biodiesel plants in the world. One of the challenges in switching to a continuous process is the simultaneous control requirement of throughput (flow), temperature, and biodiesel concentration. In the present work, a two-step homogeneous base-catalyzed transesterification process for a continuous biodiesel production plant is studied. The most relevant variables are: reaction temperature, ratio of alcohol to vegetable oil, amount of catalyst, mixing intensity (RPM), catalyst and vegetable oil used. The objective was to design a control strategy incorporating three key loops, overrides, and decoupling based on multivariate control analysis. The designed control strategy is described and simulation-based performance test results are shown.

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Reports on the topic "Multivariate Ratio"

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Zhang, Hui Jun, Oliver Linton, and Seok Young Hong. Multivariate variance ratio statistics. Cemmap, June 2014. http://dx.doi.org/10.1920/wp.cem.2014.2914.

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Anderson, T. W., and H. Hsu. Invariant Tests and Likelihood Ratio Tests for Multivariate Elliptically Contoured Distributions. Fort Belvoir, VA: Defense Technical Information Center, June 1985. http://dx.doi.org/10.21236/ada155844.

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Linton, Oliver, Seok Young Hong, and Hui Jun Zhang. An investigation into multivariate variance ratio statistics and their application to stock market predictability. Institute for Fiscal Studies, March 2015. http://dx.doi.org/10.1920/wp.cem.2015.1315.

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Boyd, Thomas J., and 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, April 2004. http://dx.doi.org/10.21236/ada422798.

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He, Miao, Zhaoqiong Zhu, Min Jiang, Xingxing Liu, Rui Wu, and 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, January 2022. http://dx.doi.org/10.37766/inplasy2022.1.0021.

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Review question / Objective: Patientor population: patients with emergence delirium; Exposure: anaesthesia and surgery; Control: patients with no emergence delirium; Outcome: risk factors; Study design: meta-analysis. Eligibility criteria: To ensure the quality of this meta-analysis, inclusion criteria was decided before we carried out the search. These criteria were: (a) Original researches that carried out in observational studies. (b)Adult patients who were extubated and recovered at PACU, operation room, or intensive care unit (ICU) after surgeries and anesthesia (including general and neuraxial anesthesia, peripheral nerve blocks and sedation). (c) Risk factors for delirium must be assessed with odds ratio (OR) with 95% confidence interval (CI). Researches must present the results of multivariate regression to be considered eligible for inclusion, since multivariate analysis results shall be used to identify variables eligible for meta-analysis. (d) Full-text available literatures.

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Clavet, Nicholas-James, Mayssun El-Attar, and Raquel Fonseca. Replacement rates of public pensions in canada: heterogeneity across socio-economic status. CIRANO, April 2022. http://dx.doi.org/10.54932/xcoz6579.

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When individuals decide to retire from the labour force, different sources of income can help to maintain consumption and welfare. One of those is public pensions. Their importance as an income source varies greatly according to socio-economic status (SES). This paper analyzes how replacement rates (RR) of public pensions (OAS and GIS) and mandatory public pension benefits (C/QPP) vary across SES by using the Longitudinal and International Study of Adults dataset (LISA). Using the longitudinal nature of this survey, we compute and compare average RRs by SES. We specifically consider the role of education and health, and we study how living arrangements can explain RRs variations. To give an idea the average RR of public pensions for individuals in bad health is 32%, while it is 21% for those who report being in good health. Including public pensions and C/QPP benefits, these numbers become 54% for those in bad health and 41% for those in good health. When estimating a multivariate regression model and controlling for past income, we find for couples, that past income does not eliminate differences in replacement ratio by individuals’ characteristics. We argue that assortative mating plays a role in explaining the variation of replacement rates across individuals’ characteristics.

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Clavet, Nicholas-James, Mayssun El-Attar, and Raquel Fonseca. Replacement rates of public pensions in canada: heterogeneity across socio-economic status. CIRANO, April 2022. http://dx.doi.org/10.54932/wsrj9253.

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When individuals decide to retire from the labour force, different sources of income can help to maintain consumption and welfare. One of those is public pensions. Their importance as an income source varies greatly according to socio-economic status (SES). This paper analyzes how replacement rates (RR) of public pensions (OAS and GIS) and mandatory public pension benefits (C/QPP) vary across SES by using the Longitudinal and International Study of Adults dataset (LISA). Using the longitudinal nature of this survey, we compute and compare average RRs by SES. We specifically consider the role of education and health, and we study how living arrangements can explain RRs variations. To give an idea the average RR of public pensions for individuals in bad health is 32%, while it is 21% for those who report being in good health. Including public pensions and C/QPP benefits, these numbers become 54% for those in bad health and 41% for those in good health. When estimating a multivariate regression model and controlling for past income, we find for couples, that past income does not eliminate differences in replacement ratio by individuals’ characteristics. We argue that assortative mating plays a role in explaining the variation of replacement rates across individuals’ characteristics.

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Tangka, Florence K. L., Sujha Subramanian, Madeleine Jones, Patrick Edwards, Sonja Hoover, Tim Flanigan, Jenya Kaganova, et al. Young Breast Cancer Survivors: Employment Experience and Financial Well-Being. RTI Press, July 2020. http://dx.doi.org/10.3768/rtipress.2020.rr.0041.2007.

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The economic burden of breast cancer for women under 50 in the United States remains largely unexplored, in part because young women make up a small proportion of breast cancer cases overall. To address this knowledge gap, we conducted a web-based survey to compare data from breast cancer survivors 18–39 years of age at first diagnosis and 40–49 years of age at first diagnosis. We administered a survey to a national convenience sample of 416 women who were 18–49 years of age at the time of their breast cancer diagnosis. We analyzed factors associated with financial decline using multivariate regression. Survivors 18–39 years of age at first diagnosis were more likely to report Stage II–IV breast cancer (P<0.01). They also quit their jobs more often (14.6%) than older survivors (4.4%; P<0.01) and faced more job performance issues (55.7% and 42.8%, respectively; P=0.02). For respondents in both groups, financial decline was more likely if the survivor had at least one comorbid condition (odds ratios: 2.36–3.21) or was diagnosed at Stage II–IV breast cancer (odds ratios: 2.04–3.51).

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