Relevant bibliographies by topics / Marginal parameters

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Marginal parameters'

Author: Grafiati
Published: 9 March 2023
Last updated: 10 March 2023

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Journal articles on the topic "Marginal parameters"

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Hudson, Suzanne, and Paul W. Vos. "Marginal information for expectation parameters." Canadian Journal of Statistics 28, no. 4 (December 2000): 875–86. http://dx.doi.org/10.2307/3315922.

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Kharroubi, Samer A. "Approximate marginal densities of independent parameters." Statistics 46, no. 4 (February 2, 2011): 459–71. http://dx.doi.org/10.1080/02331888.2010.540667.

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De Bernardo, Maddalena, Palmiro Cornetta, Giuseppe Marotta, and Nicola Rosa. "Corneal biomechanical parameters in pellucid marginal degeneration." Journal of Current Ophthalmology 30, no. 3 (September 2018): 280. http://dx.doi.org/10.1016/j.joco.2018.06.002.

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Mishra, Ambika P., Nicol S. Harper, and Jan W. H. Schnupp. "Exploring the distribution of statistical feature parameters for natural sound textures." PLOS ONE 16, no. 6 (June 23, 2021): e0238960. http://dx.doi.org/10.1371/journal.pone.0238960.

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Sounds like “running water” and “buzzing bees” are classes of sounds which are a collective result of many similar acoustic events and are known as “sound textures”. A recent psychoacoustic study using sound textures has reported that natural sounding textures can be synthesized from white noise by imposing statistical features such as marginals and correlations computed from the outputs of cochlear models responding to the textures. The outputs being the envelopes of bandpass filter responses, the ‘cochlear envelope’. This suggests that the perceptual qualities of many natural sounds derive directly from such statistical features, and raises the question of how these statistical features are distributed in the acoustic environment. To address this question, we collected a corpus of 200 sound textures from public online sources and analyzed the distributions of the textures’ marginal statistics (mean, variance, skew, and kurtosis), cross-frequency correlations and modulation power statistics. A principal component analysis of these parameters revealed a great deal of redundancy in the texture parameters. For example, just two marginal principal components, which can be thought of as measuring the sparseness or burstiness of a texture, capture as much as 64% of the variance of the 128 dimensional marginal parameter space, while the first two principal components of cochlear correlations capture as much as 88% of the variance in the 496 correlation parameters. Knowledge of the statistical distributions documented here may help guide the choice of acoustic stimuli with high ecological validity in future research.
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Domke, J. "Learning Graphical Model Parameters with Approximate Marginal Inference." IEEE Transactions on Pattern Analysis and Machine Intelligence 35, no. 10 (October 2013): 2454–67. http://dx.doi.org/10.1109/tpami.2013.31.

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Evans, Robin J., and Thomas S. Richardson. "Marginal log-linear parameters for graphical Markov models." Journal of the Royal Statistical Society: Series B (Statistical Methodology) 75, no. 4 (July 3, 2013): 743–68. http://dx.doi.org/10.1111/rssb.12020.

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Allenby, Greg M., and Peter E. Rossi. "A marginal-predictive approach to identifying household parameters." Marketing Letters 4, no. 3 (July 1993): 227–39. http://dx.doi.org/10.1007/bf00999229.

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AL-Moisheer, A. S., Refah Mohammed Alotaibi, Ghadah A. Alomani, and H. Rezk. "Bivariate Mixture of Inverse Weibull Distribution: Properties and Estimation." Mathematical Problems in Engineering 2020 (March 28, 2020): 1–12. http://dx.doi.org/10.1155/2020/5234601.

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In this study, we construct a mixture of bivariate inverse Weibull distribution. We assumed that the parameters of two marginals have Bernoulli distributions. Several properties of the proposed model are obtained, such as probability marginal density function, probability marginal cumulative function, the product moment, the moment of the two variables x and y, the joint moment-generating function, and the correlation between x and y. The real dataset has been analyzed. We observed that the mixture bivariate inverse Weibull distribution provides a better fit than the other model.
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Taufer, Emanuele. "Estimation of marginal parameters of SUP-OU processes with long range dependence." International Journal of Advanced Statistics and Probability 4, no. 2 (October 10, 2016): 102. http://dx.doi.org/10.14419/ijasp.v4i2.6722.

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Superpositions of Ornstein Uhlenbeck processes provide convenient ways to build stationary processes with given marginal distributions and long range dependence. After reviewing some of the basic features, we present several examples of processes with non Gaussian marginal distributions. Estimation of the parameters of the marginal distribution is undertaken by means of a characteristic function technique. We provide the relevant asymptotic theory as well as results of simulations and real data applications.
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Chisoi, Anca, Mariana Aşchie, and Manuela Enciu. "Morphometric Characterization of Marginal Zone Lymphoma." ARS Medica Tomitana 21, no. 1 (February 1, 2015): 17–21. http://dx.doi.org/10.1515/arsm-2015-0014.

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Abstract The morphometry in histopathology is used to characterize cell populations belonging to different tissues and to identify differences in their parameters with prognostic implications. To achieve morphometric examination were selected 6 of 8 cases identified as marginal zone lymphoma. For each case analysis was done on five fields, for each field measuring the parameters of 20 cells. The studied parameters were for cytoplasm: cytoplasmic area, maximum and minimum cytoplasmic diameter, cytoplasmic perimeter; for nucleus were measured: nuclear area, minimum and maximum nuclear diameter, nuclear perimeter, nuclear contour index, nuclear ellipticity index, nuclear irregularity index. Also the nucleo-cytoplasmic ratio was calculated in all studied cases. Marginal zone lymphoma is characterized in terms of morphometric parameters by small cytoplasmic and nuclear area, and small nucleo-cytoplasmatic ratio of about 1:1. Nuclear contour index is small, accompanied by a large ellipticity index and an small index of nuclear irregularity. Standard deviations for measured morphometric parameters are variable, having high values for cytoplasmic and nuclear area, highlighting the polymorphic nature of the cells. Morphometric aspects, with corresponding microscopic aspects of large and small lymphocyte proliferation with cleaved and uncleaved nuclei, fit this form of lymphoma in terms of clinical outcome in indolent lymphomas category.
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Dissertations / Theses on the topic "Marginal parameters"

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NICOLUSSI, FEDERICA. "Marginal parametrizations for conditional independence models and graphical models for categorical data." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2013. http://hdl.handle.net/10281/43679.

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The graphical models (GM) for categorical data are models useful to representing conditional independencies through graphs. The parametric marginal models for categorical data have useful properties for the asymptotic theory. This work is focused on nding which GMs can be represented by marginal parametrizations. Following theorem 1 of Bergsma, Rudas and Németh [9], we have proposed a method to identify when a GM is parametrizable according to a marginal model. We have applied this method to the four types of GMs for chain graphs, summarized by Drton [22]. In particular, with regard to the so-called GM of type II and GM of type III, we have found the subclasses of these models which are parametrizable with marginal models, and therefore they are smooth. About the so-called GM of type I and GM of type IV, in the literature it is known that these models are smooth and we have provided new proof of this result. Finally we have applied the mean results concerning the GM of type II on the EVS data-set.
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Modenesi, Bernardo Andrade Lyrio. "Bounds on policy relevant parameters with discrete policy variation." reponame:Repositório Institucional do FGV, 2015. http://hdl.handle.net/10438/13857.

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When estimating policy parameters, also known as treatment effects, the assignment to treatment mechanism almost always causes endogeneity and thus bias many of these policy parameters estimates. Additionally, heterogeneity in program impacts is more likely to be the norm than the exception for most social programs. In situations where these issues are present, the Marginal Treatment Effect (MTE) parameter estimation makes use of an instrument to avoid assignment bias and simultaneously to account for heterogeneous effects throughout individuals. Although this parameter is point identified in the literature, the assumptions required for identification may be strong. Given that, we use weaker assumptions in order to partially identify the MTE, i.e. to stablish a methodology for MTE bounds estimation, implementing it computationally and showing results from Monte Carlo simulations. The partial identification we perfom requires the MTE to be a monotone function over the propensity score, which is a reasonable assumption on several economics' examples, and the simulation results shows it is possible to get informative even in restricted cases where point identification is lost. Additionally, in situations where estimated bounds are not informative and the traditional point identification is lost, we suggest a more generic method to point estimate MTE using the Moore-Penrose Pseudo-Invese Matrix, achieving better results than traditional methods.
A estimação de parâmetros relevantes no contexto de intervenções políticas, também conhecidos como efeitos de tratamento, enfrenta diversos problemas práticos como o viés relacionado ao mecanismo de atribuição do status de tratamento. Adicionalmente, efeitos heterogênos na literatura de Avaliação de Impactos é mais comum que efeitos homogêneos. Em situações nas quais estes problemas estão presentes, a estimação do Efeito Marginal de Tratamento (MTE) emprega o método de variáveis instrumentais para contornar o viés de seleção ao tratamento, obtendo ao mesmo tempo efeitos heterogêneos. Mesmo que a literatura identifique pontualmente este parâmetro, as hipóteses por trás da identificação são costumeiramente restritivas. Neste trabalho pretende-se afrouxar as hipóteses vigentes na literatura de modo a obter identificação parcial do MTE, requerendo apenas monotonicidade do mesmo ao longo das diferentes propensões ao tratamento, o que é comum em diversos exemplos da literatura econômica. Simulações de Monte Carlo são performadas, resultando em limites para o MTE que se mostram informativos, mesmo em situações restritas nas quais a tradicional identificação pontual é perdida. Complementarmente, em situações quando a identificação parcial não é informativa e a tradicional ponto identificação é perdida, propomos a ponto identificação utilizando a matrix pseudo inversa de Moore-Penrose. Esta metodologia prescinde da hipótese de monotonicidade e resulta em melhores estimativas quando comparada aos métodos tradicionais.
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野口, 裕之, and Hiroyuki G. NOGUCHI. "<原著>共通被験者デザインにおける等化係数の周辺最尤法による推定." 名古屋大学教育学部, 1990. http://hdl.handle.net/2237/3827.

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Thompson, Vanessa Marie. "Marginal Bayesian parameter estimation in the multidimensional generalized graded unfolding model." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/53411.

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The Multidimensional Generalized Graded Unfolding Model (MGGUM) is a proximity-based, noncompensatory item response theory (IRT) model with applications in the context of attitude, personality, and preference measurement. Model development used fully Bayesian Markov Chain Monte Carlo (MCMC) parameter estimation (Roberts, Jun, Thompson, & Shim, 2009a; Roberts & Shim, 2010). Challenges can arise while estimating MGGUM parameters using MCMC where the meaning of dimensions may switch during the estimation process and difficulties in obtaining informative starting values may lead to increased identification of local maxima. Furthermore, researchers must contend with lengthy computer processing time. It has been shown alternative estimation methods perform just as well as, if not better than, MCMC in the unidimensional Generalized Graded Unfolding Model (GGUM; Roberts & Thompson, 2011) with marginal maximum a posteriori (MMAP) item parameter estimation paired with expected a posteriori (EAP) person parameter estimation being a viable alternative. This work implements MMAP/EAP parameter estimation in the multidimensional model. Additionally, item location initial values are derived from detrended correspondence analysis (DCA) based on previous implementation of correspondence analysis in the GGUM (Polak, 2011). A parameter recovery demonstrates the accuracy of two-dimensional MGGUM MMAP/EAP parameter estimates and a comparative analysis of MMAP/EAP and MCMC demonstrates equal accuracy, yet much improved efficiency of the former method. Analysis of real attitude measurement data also provides an illustrative application of the model.
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Do, Hoan. "Parameter Recovery for the Four-Parameter Unidimensional Binary IRT Model: A Comparison of Marginal Maximum Likelihood and Markov Chain Monte Carlo Approaches." Ohio University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1616202942083398.

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Wu, Yi-Fang. "Accuracy and variability of item parameter estimates from marginal maximum a posteriori estimation and Bayesian inference via Gibbs samplers." Diss., University of Iowa, 2015. https://ir.uiowa.edu/etd/5879.

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Item response theory (IRT) uses a family of statistical models for estimating stable characteristics of items and examinees and defining how these characteristics interact in describing item and test performance. With a focus on the three-parameter logistic IRT (Birnbaum, 1968; Lord, 1980) model, the current study examines the accuracy and variability of the item parameter estimates from the marginal maximum a posteriori estimation via an expectation-maximization algorithm (MMAP/EM) and the Markov chain Monte Carlo Gibbs sampling (MCMC/GS) approach. In the study, the various factors which have an impact on the accuracy and variability of the item parameter estimates are discussed, and then further evaluated through a large scale simulation. The factors of interest include the composition and length of tests, the distribution of underlying latent traits, the size of samples, and the prior distributions of discrimination, difficulty, and pseudo-guessing parameters. The results of the two estimation methods are compared to determine the lower limit--in terms of test length, sample size, test characteristics, and prior distributions of item parameters--at which the methods can satisfactorily recover item parameters and efficiently function in reality. For practitioners, the results help to define limits on the appropriate use of the BILOG-MG (which implements MMAP/EM) and also, to assist in deciding the utility of OpenBUGS (which carries out MCMC/GS) for item parameter estimation in practice.
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Svoboda, Ondřej. "Využití Poissonova rozdělení pro předpovědi výsledků sportovních utkání." Master's thesis, Vysoká škola ekonomická v Praze, 2017. http://www.nusl.cz/ntk/nusl-359303.

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The aim of this master thesis is to verify possibility to use Poisson distribution for predicting soccer matches. At first for analysis is applied the original model from English statisticians Mark J. Dixon and Stuart G. Coles from 1997. Thereafter the model is extended in the thesis. All models are based on the maximum likelihood method. Chosen league for deducing conclusions is the first English league - Premier League. The matches are played in the period from season 2004/2005 to half of season 2015/2016. For identification of models performance are used the most market odds from American bookmaker Pinnacle. In the theoretical part are described models and statistical methods that are used in the practical part. In the practical part are realized calculations. Counted performance of models is based on profit from market odds. In the period ex-post are calculated optimum model parameters that are used in the ex-ante period, where is calculated performance of the model. The thesis answers question: Are these models gaining from public database effective in modern age?
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Coppola, Gregory Francis. "Iterative parameter mixing for distributed large-margin training of structured predictors for natural language processing." Thesis, University of Edinburgh, 2015. http://hdl.handle.net/1842/10451.

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The development of distributed training strategies for statistical prediction functions is important for applications of machine learning, generally, and the development of distributed structured prediction training strategies is important for natural language processing (NLP), in particular. With ever-growing data sets this is, first, because, it is easier to increase computational capacity by adding more processor nodes than it is to increase the power of individual processor nodes, and, second, because data sets are often collected and stored in different locations. Iterative parameter mixing (IPM) is a distributed training strategy in which each node in a network of processors optimizes a regularized average loss objective on its own subset of the total available training data, making stochastic (per-example) updates to its own estimate of the optimal weight vector, and communicating with the other nodes by periodically averaging estimates of the optimal vector across the network. This algorithm has been contrasted with a close relative, called here the single-mixture optimization algorithm, in which each node stochastically optimizes an average loss objective on its own subset of the training data, operating in isolation until convergence, at which point the average of the independently created estimates is returned. Recent empirical results have suggested that this IPM strategy produces better models than the single-mixture algorithm, and the results of this thesis add to this picture. The contributions of this thesis are as follows. The first contribution is to produce and analyze an algorithm for decentralized stochastic optimization of regularized average loss objective functions. This algorithm, which we call the distributed regularized dual averaging algorithm, improves over prior work on distributed dual averaging by providing a simpler algorithm (used in the rest of the thesis), better convergence bounds for the case of regularized average loss functions, and certain technical results that are used in the sequel. The central contribution of this thesis is to give an optimization-theoretic justification for the IPM algorithm. While past work has focused primarily on its empirical test-time performance, we give a novel perspective on this algorithm by showing that, in the context of the distributed dual averaging algorithm, IPM constitutes a convergent optimization algorithm for arbitrary convex functions, while the single-mixture distribution algorithm is not. Experiments indeed confirm that the superior test-time performance of models trained using IPM, compared to single-mixture, correlates with better optimization of the objective value on the training set, a fact not previously reported. Furthermore, our analysis of general non-smooth functions justifies the use of distributed large-margin (support vector machine [SVM]) training of structured predictors, which we show yields better test performance than the IPM perceptron algorithm, the only version of the IPM to have previously been given a theoretical justification. Our results confirm that IPM training can reach the same level of test performance as a sequentially trained model and can reach better accuracies when one has a fixed budget of training time. Finally, we use the reduction in training time that distributed training allows to experiment with adding higher-order dependency features to a state-of-the-art phrase-structure parsing model. We demonstrate that adding these features improves out-of-domain parsing results of even the strongest phrase-structure parsing models, yielding a new state-of-the-art for the popular train-test pairs considered. In addition, we show that a feature-bagging strategy, in which component models are trained separately and later combined, is sometimes necessary to avoid feature under-training and get the best performance out of large feature sets.
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Sivaramakrishnan, Jayaram. "Unsupervised probabilistic and kernel regression methods for anomaly detection and parameter margin prediction of industrial design." Thesis, Sivaramakrishnan, Jayaram (2021) Unsupervised probabilistic and kernel regression methods for anomaly detection and parameter margin prediction of industrial design. PhD thesis, Murdoch University, 2021. https://researchrepository.murdoch.edu.au/id/eprint/62536/.

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One of the significant challenges facing industrial plant design is ensuring the integrity of massive design datasets generated during the project execution. This work is motivated by personal experience of data integrity issues during projects caused by insufficient automation affecting the quality of deliverables. Therefore, this project sought automated solutions for detecting anomalies in industrial design data in the form of outliers. Several novel methods are proposed, based on the Hidden Markov Model (HMM) and a modified General Regression Neural Network called the Margin-Based GRNN (MB-GRNN) along with optimisation techniques that minimise computation time. An HMM was used for validating process plant tag numbers using a self-learning approach. Results from experimental data show that HMM performance is equivalent to that of a custom-made design rule checking algorithm. The choice of components in industrial design involves setting specific design parameters that typically must reside inside permissible ranges called “design margins”. The MB-GRNN has the ability to estimate these permissible margins directly from design data and indicate potential design errors resulting from the invalid choice of design parameters by identifying data points outside of the estimated margins as outliers. The extremal permissible margin boundaries are determined by “stretching out” the upper and lower GRNN surfaces using an iterative application of stretch factors (a second kernel weighting factor). The method creates a variable insensitive band surrounding the data cloud, interlinked with the normal regression function, providing upper and lower margin boundaries. These boundaries can then be used to determine outliers and to predict a range of permissible values of design parameters during design. This method was compared to Parzen-Windows and another proximity-based method. The MB-GRNN also benefits from a modified algorithm for estimating the smoothing parameter using a combination of clustering, k-nearest neighbour, and localised covariance matrix. The computation time for this difficult task is minimised using a new derivative-based method that was tested successfully using a range of root-finding functions. The efficacy of the MB-GRNN and associated optimisation techniques were verified using three multivariate design datasets. The experimentation shows that the regression-based outlier classification approach used in this project complements the existing Parzen density-based method. These methods used in combination are intended for implementation as a decision support system for checking the quality of industrial design data to help minimise design and implementation costs. It is expected that the unsupervised techniques presented in this research work will benefit from the ever-increasing automation of industrial design processes.
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Kallweit, Michael [Verfasser], Hans Ulrich [Gutachter] Simon, and Eike [Gutachter] Kiltz. "Margin parameters for linear classification and their connections to selected complexity measures / Michael Kallweit ; Gutachter: Hans Ulrich Simon, Eike Kiltz ; Fakultät für Mathematik." Bochum : Ruhr-Universität Bochum, 2014. http://d-nb.info/1226426549/34.

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Books on the topic "Marginal parameters"

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Heikki, Jussila, Mutambirwa Chris C, Majoral i. Moliné Roser, and International Geographical Union, eds. Marginality in space--past, present and future: Theoretical and methodological aspects of cultural, social and economic parameters of marginal and critical regions. Aldershot, Hants, England: Ashgate, 1999.

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(Editor), Heikki Jussila, Roser Majoral (Editor), and Chris C. Mutambirwa (Editor), eds. Marginality in Space - Past, Present and Future: Theoretical and Methodological Aspects of Cultural, Social and Economic Parameters of Marginal and Critical ... of Marginal and Critical Regions). Ashgate Publishing, 1999.

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Marginality in Space - Past, Present and Future: Theoretical and Methodological Aspects of Cultural, Social and Economic Parameters of Marginal and Critical Regions. Taylor & Francis Group, 2018.

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Majoral, Roser, Chris C. Mutambirwa, and Heikki Jussila. Marginality in Space - Past, Present and Future: Theoretical and Methodological Aspects of Cultural, Social and Economic Parameters of Marginal and Critical Regions. Taylor & Francis Group, 2019.

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Majoral, Roser, Chris C. Mutambirwa, and Heikki Jussila. Marginality in Space - Past, Present and Future: Theoretical and Methodological Aspects of Cultural, Social and Economic Parameters of Marginal and Critical Regions. Taylor & Francis Group, 2019.

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Majoral, Roser, Chris C. Mutambirwa, and Heikki Jussila. Marginality in Space - Past, Present and Future: Theoretical and Methodological Aspects of Cultural, Social and Economic Parameters of Marginal and Critical Regions. Taylor & Francis Group, 2019.

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Majoral, Roser, Chris C. Mutambirwa, and Heikki Jussila. Marginality in Space - Past, Present and Future: Theoretical and Methodological Aspects of Cultural, Social and Economic Parameters of Marginal and Critical Regions. Taylor & Francis Group, 2019.

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Biggs, Kristian Pedersen. Spatial variability of the ambient noise field associated with the Marginal Ice Zone and its relationship to environmental parameters. 1988.

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Huffaker, Ray, Marco Bittelli, and Rodolfo Rosa. Empirically Detecting Causality. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198782933.003.0008.

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Phenomenological models mathematically describe relationships among empirically observed phenomena without attempting to explain underlying mechanisms. Within the context of NLTS, phenomenological modeling goes beyond phase space reconstruction to extract equations governing real-world system dynamics from a single or multiple observed time series. Phenomenological models provide several benefits. They can be used to characterize the dynamics of variable interactions; for example, whether an incremental increase in one variable drives a marginal increase/decrease in the growth rate of another, and whether these dynamic interactions follow systematic patterns over time. They provide an analytical framework for data driven science still searching for credible theoretical explanation. They set a descriptive standard for how the real world operates so that theory is not misdirected in explaining fanciful behavior. The success of phenomenological modeling depends critically on selection of governing parameters. Model dimensionality, and the time delays used to synthesize dynamic variables, are guided by statistical tests run for phase space reconstruction. Other regression and numerical integration parameters can be set on a trial and error basis within ranges providing numerical stability and successful reproduction of empirically-detected dynamics. We illustrate phenomenological modeling with solutions of the Lorenz model so that we can recognize the dynamics that need to be reproduced.
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Bygrave, Lee A. Hardwiring Privacy. Edited by Roger Brownsword, Eloise Scotford, and Karen Yeung. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199680832.013.52.

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This chapter examines regulatory efforts to ensure that due account is taken of privacy and related interests in the development of information systems such that these interests are, in effect, integrated (or ‘hardwired’) into the resulting systems. Such efforts are typically described in terms of ‘Privacy by Design’ and ‘Data Protection by Design’. The basic argument advanced in the chapter is that such efforts are unlikely to gain broad traction, at least in the short term, despite current moves to provide them with increased legal support. This is due to a broad range of factors the most important of which is that any ambitious privacy-hardwiring efforts will clash with powerful business and state interests at the same time as they remain marginal to the concerns of most consumers and engineers. This marginality is exacerbated by poor communication of such efforts’ parameters, methodologies and requirements.
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Book chapters on the topic "Marginal parameters"

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Mariel, Petr, David Hoyos, Jürgen Meyerhoff, Mikolaj Czajkowski, Thijs Dekker, Klaus Glenk, Jette Bredahl Jacobsen, et al. "Calculating Marginal and Non-marginal Welfare Measures." In Environmental Valuation with Discrete Choice Experiments, 103–10. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62669-3_7.

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AbstractThis chapter focuses on the calculation of marginal and non-marginal welfare measures. It outlines how the calculation of welfare measures is related to the specified model and the assumptions underlying that model. It further describes how the calculation of these measures is affected by the inclusion of preference heterogeneity, including the incorporation of interaction terms to capture observed preference heterogeneity or random parameters to capture unobserved preference heterogeneity. Finally, it discusses how these measures can be aggregated and compared.
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Kim, Seock-Ho, Yu Bao, Erin Horan, Meereem Kim, and Allan S. Cohen. "Gauss–Hermite Quadrature in Marginal Maximum Likelihood Estimation of Item Parameters." In Quantitative Psychology Research, 43–58. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19977-1_4.

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Jeong, Hae-Duck J., Jong-Suk R. Lee, and Hyoung-Woo Park. "Teletraffic Generation of Self-Similar Processes with Arbitrary Marginal Distributions for Simulation: Analysis of Hurst Parameters." In Computational Science and Its Applications – ICCSA 2004, 827–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24767-8_87.

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Manzi, Hilda, and Joseph P. Gweyi-Onyango. "Agro-ecological Lower Midland Zones IV and V in Kenya Using GIS and Remote Sensing for Climate-Smart Crop Management." In African Handbook of Climate Change Adaptation, 965–91. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-45106-6_35.

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AbstractFood production in Kenya and Africa in recent past has experienced vagaries of weather fluctuations which ultimately have affected crop yield. Farming in Kenya is localized in specific Agro-ecological zones, hence understanding crop growth responses in particular regions is crucial in planning and management for purposes of accelerating adoption. A number of strategies for adoption and adaptation to changing weather patterns have been deployed yet only limited challenges have been partially addressed or managed. This chapter examines previous methods used in classifying agro-ecological zones and further provides additional insightful parameters that can be adopted to enable farmers understand and adapt better to the current variable and unpredictable cropping seasons. The chapter scrutinizes past and current documented information on agro-ecological zonal valuations coupled with the use of earth observation components such as air temperature at surface, land surface temperature, evapotranspiration, soil, temperature, and soil and moisture content in order to better understand and effectively respond to new phenomena occurring as a result of climate change in the marginal agricultural areas. Significant variations in precipitation, ambient temperature, soil moisture content, and soil temperature become evident when earth observation data are used in evaluation of agro-ecological lower midland zones IV and V. The said variations cut across areas within the agro-ecological zones that have been allocated similar characteristics when assigning cropping seasons. The chapter summarizes the outcomes of various streams of contributions that have reported significant shifts or changes in rainfall and temperature patterns across Kenya and wider Eastern Africa region. The chapter highlights the need for re-evaluation of the agro-ecological zones based on the recent earth observation datasets in their diversity. The research emphasizes the use of multiple climate and soil-related parameters in understanding climate change in the other marginal areas of Kenya.
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Manzi, Hilda, and Joseph P. Gweyi-Onyango. "Agro-ecological Lower Midland Zones IV and V in Kenya Using GIS and Remote Sensing for Climate-Smart Crop Management." In African Handbook of Climate Change Adaptation, 1–27. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42091-8_35-1.

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AbstractFood production in Kenya and Africa in recent past has experienced vagaries of weather fluctuations which ultimately have affected crop yield. Farming in Kenya is localized in specific Agro-ecological zones, hence understanding crop growth responses in particular regions is crucial in planning and management for purposes of accelerating adoption. A number of strategies for adoption and adaptation to changing weather patterns have been deployed yet only limited challenges have been partially addressed or managed. This chapter examines previous methods used in classifying agro-ecological zones and further provides additional insightful parameters that can be adopted to enable farmers understand and adapt better to the current variable and unpredictable cropping seasons. The chapter scrutinizes past and current documented information on agro-ecological zonal valuations coupled with the use of earth observation components such as air temperature at surface, land surface temperature, evapotranspiration, soil, temperature, and soil and moisture content in order to better understand and effectively respond to new phenomena occurring as a result of climate change in the marginal agricultural areas. Significant variations in precipitation, ambient temperature, soil moisture content, and soil temperature become evident when earth observation data are used in evaluation of agro-ecological lower midland zones IV and V. The said variations cut across areas within the agro-ecological zones that have been allocated similar characteristics when assigning cropping seasons. The chapter summarizes the outcomes of various streams of contributions that have reported significant shifts or changes in rainfall and temperature patterns across Kenya and wider Eastern Africa region. The chapter highlights the need for re-evaluation of the agro-ecological zones based on the recent earth observation datasets in their diversity. The research emphasizes the use of multiple climate and soil-related parameters in understanding climate change in the other marginal areas of Kenya.
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Qin, Jing. "Connections Among Marginal Likelihood, Conditional Likelihood and Empirical Likelihood." In Biased Sampling, Over-identified Parameter Problems and Beyond, 331–51. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4856-2_18.

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Soh, Y. C., and Y. K. Foo. "Stability Margins of Perturbed Systems." In Robustness of Dynamic Systems with Parameter Uncertainties, 13–21. Basel: Birkhäuser Basel, 1992. http://dx.doi.org/10.1007/978-3-0348-7268-3_2.

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Genest, Christian, and Bas J. M. Werker. "Conditions for the Asymptotic Semiparametric Efficiency of an Omnibus Estimator of Dependence Parameters in Copula Models." In Distributions With Given Marginals and Statistical Modelling, 103–12. Dordrecht: Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-017-0061-0_12.

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Burton, Paul W., and Peter C. Marrow. "Seismic Hazard and Earthquake Source Parameters in the North Sea." In Earthquakes at North-Atlantic Passive Margins: Neotectonics and Postglacial Rebound, 633–64. Dordrecht: Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-009-2311-9_36.

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Zhao, Yue, and Jinwen Ma. "Kernel Parameter Optimization for KFDA Based on the Maximum Margin Criterion." In Advances in Neural Networks – ISNN 2014, 330–37. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12436-0_37.

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Conference papers on the topic "Marginal parameters"

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Meng, Zhaoshi, Dennis Wei, Alfred O. Hero, and Ami Wiesel. "Marginal likelihoods for distributed estimation of graphical model parameters." In 2013 IEEE 5th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP). IEEE, 2013. http://dx.doi.org/10.1109/camsap.2013.6714010.

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Harber, Keith, and Steve Brockett. "Marginal RF Gain Investigation and Root Cause Determination." In ISTFA 2013. ASM International, 2013. http://dx.doi.org/10.31399/asm.cp.istfa2013p0095.

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Abstract This paper outlines the failure analysis of a Radio Frequency only (RF-only) failure on a complex Multimode Multiband Power Amplifier (MMPA) module, where slightly lower gain was observed in one mode of operation. 2 port S-parameter information was collected and utilized to help localize the circuitry causing the issue. A slight DC electrical difference was observed, and simulation was utilized to confirm that difference was causing the observed S-parameters. Physical analysis uncovered a very visible cause for the RF-only failure.
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Privalov, Alexander Yu, and Alexander V. Blagov. "Some Models Parameters Calculation For Simulation Of Network Traffic Marginal Distribution And Self-Similarity." In 23rd European Conference on Modelling and Simulation. ECMS, 2009. http://dx.doi.org/10.7148/2009-0018-0024.

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Hou, Qinzhong, Songcheng Mu, and Mengzhu Zhang. "Marginal Effects for Random Parameters Logit Models: A Case Study of Crash Severity Analysis." In 22nd COTA International Conference of Transportation Professionals. Reston, VA: American Society of Civil Engineers, 2022. http://dx.doi.org/10.1061/9780784484265.167.

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Fouques, Se´bastien, Dag Myrhaug, and Finn Gunnar Nielsen. "Seasonal Modelling of Multivariate Distributions of Metocean Parameters." In ASME 2002 21st International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2002. http://dx.doi.org/10.1115/omae2002-28048.

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Statistical information about the joint occurrence of metocean parameters is of importance for many offshore activities. For instance, in marine operations, environmental limitations may be brought about by both wind and wave conditions. Thus, knowledge of their joint occurrence is important as the persistence duration and the seasonal dependence of wind and waves appear to be of large interest. However, such a modelling becomes difficult as the number of considered variables increases, especially when utilizing a common parameterization of some conditional distributions. This paper proposes a general methodology that aims at modelling seasonal joint distributions of n such parameters from their correlation structure and the n marginal distributions fitted by generalized gamma ones. Two methods are proposed in order to derive an approximate joint distribution from the modelled margins. The first one matches the correlation matrix only, whereas the second one, which is based on a multivariate Hermite polynomials expansion of the multinormal distribution, is able to match joint moments of order higher than two. However, more restrictive conditions are shown by the latter. An application to the simple example of the joint occurrence of significant wave height and the mean wind velocity at the 10m elevation is used to illustrate the methods. Eventually, examples of applications like simultaneous persistence of wind and wave conditions as well as seastate forecasting from statistics are given.
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Nguyen, Kim-Doang, Harry Dankowicz, and Naira Hovakimyan. "Marginal Stability in ℒ1-Adaptive Control of Manipulators." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-12744.

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This paper presents a preliminary analysis of the robustness of a recently-proposed adaptive controller for robot manipulators based on the ℒ1 control paradigm. Here, the use of a low-pass filter in the control input decouples the estimation loop from the control loop, thereby facilitating an arbitrary increase of estimation rates (limited only by hardware) without sacrificing robustness. Tuning of the filter also allows for shaping the nominal response and enhancing the system’s robustness. The paper further demonstrates improvements in the critical time delay associated with a static reference input achieved through the introduction of time delay in the state-predictor formulation. Guided by results from the theory of single-input-single-output ℒ1 control systems, a linear, time-invariant system is proposed in order to derive a conservative lower bound on the system’s actuator critical time delay for static reference input in the limit of large estimation gains, as an indicator of robustness. Finally, a numerical method is proposed for quantifying the robustness against time delay of the system’s response to a given static reference input based on techniques of parameter continuation. This method computes the critical time delay at which local stability is lost in a Hopf bifurcation. The dependence of this critical time delay on control parameters, such as adaptive gains and filter bandwidth, is here obtained using advanced algorithms for computing approximate covers of implicitly defined manifolds.
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An, Dawn, and Joo-Ho Choi. "Improved MCMC Method for Parameter Estimation Based on Marginal Probability Density Function." In ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/detc2011-48784.

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In many engineering problems, sampling is often used to estimate and quantify the probability distribution of uncertain parameters during the course of Bayesian framework, which is to draw proper samples that follow the probabilistic feature of the parameters. Among numerous approaches, Markov Chain Monte Carlo (MCMC) has gained the most popularity due to its efficiency and wide applicability. The MCMC, however, does not work well in the case of increased parameters and/or high correlations due to the difficulty of finding proper proposal distribution. In this paper, a method employing marginal probability density function (PDF) as a proposal distribution is proposed to overcome these problems. Several engineering problems which are formulated by Bayesian approach are addressed to demonstrate the effectiveness of proposed method.
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Silva, Camilo F., Kah Joon Yong, and Luca Magri. "Thermoacoustic Modes of Quasi-1D Combustors in the Region of Marginal Stability." In ASME Turbo Expo 2018: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/gt2018-76921.

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It may be generally believed that the thermoacoustic eigenfrequencies of a combustor with fully acoustically reflecting boundary conditions depend on both flame dynamics and geometry of the system. In this work, we show that there are situations where this understanding does not strictly apply. The purpose of this study is twofold. In the first part, we show that the resonance frequencies of two premixed combustors with fully acoustically reflecting boundary conditions in the region of marginal stability depend only on the parameters of the flame dynamics, but do not depend on the combustor’s geometry. This is shown by means of a parametric study, where the time delay and the interaction index of the flame response are varied and the resulting complex eigenfrequency locus is shown. Assuming longitudinal acoustics and a low Mach number, a quasi-1D Helmholtz solver is utilized. The time delay and interaction index of the flame response are parametrically varied to calculate the complex eigenfrequency locus. It is found that all the eigenfrequency trajectories cross the real axis at a resonance frequency that depends only on the time delay. Such marginally stable frequencies are independent of the resonant cavity modes of the two combustors, i.e. the passive thermoacoustic modes. In the second part, we exploit the aforementioned observation to evaluate the critical flame gain required for the systems to become unstable at four eigenfrequencies located in the marginally stable region. A computationally-efficient method is proposed. The key ingredient is to consider both direct and adjoint eigenvectors associated with the four eigenfrequencies. Hence, the sensitivity of the eigenfrequencies to changes in the gain at the region of marginal stability is evaluated with cheap and accurate calculations. This work contributes to the understanding of thermoacoustic stability of combustors. In the same manner, the understanding of the nature of distinct resonance frequencies in unstable combustors may be enhanced by employing the analysis of the eigenfrequency locus here reported.
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Bordalo, Ana, and Ana paula Rainha. "Marginal Architecture [How will we live together?] - a process under construction…" In 4th International Conference of Contemporary Affairs in Architecture and Urbanism – Full book proceedings of ICCAUA2020, 20-21 May 2021. Alanya Hamdullah Emin Paşa University, 2021. http://dx.doi.org/10.38027/iccaua2021273n11.

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The organization of territory and cities is a structuring element for the management of epidemic crises. The existence of basic sanitary structures is, nowadays, an acquired and determined factor for the healthiness of territories, as well as for the structural contribution to the well-being of the populations. Since the 19th century epidemic crises established health parameters for Architecture and Urbanism, which are still a reference today. Almost after one hundred years, where the questions of salubrity were supposed to be consolidated, we find that, suddenly, without advice, new alarm bells rings: we found that the world was not prepared to be closed in its “housing units”. Assuming Portimão as an urban laboratory and as a waterfront city, we will present the process developed for studies, searching for proposals witch solutions look for a contemporary assignment, which imposes to Architecture a principle settled on options of sustainability, impermanence, reuse and recycling.
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Tao, Shanshan, Sheng Dong, and Yinghui Xu. "Design Parameter Estimation of Wave Height and Wind Speed With Bivariate Copulas." In ASME 2013 32nd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/omae2013-10519.

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The data of annual extreme wave height and corresponding wind speed at a platform in Bohai Bay is hindcasted by a numerical model from 1970 to 1993. Common-used design probability distributions, such as Gumbel distribution, Weibull distribution, and lognormal distribution are applied to fit the data of extreme wave height and concomitant wind speed, respectively. Then the best-fitted marginal distributions of annual extreme wave height and wind speed can be selected. Bivariate normal copula and Frank copula are utilized to construct joint distribution of these two random variables. Based on empirical base shear equation of the on-site fixed jacket platform, the maximum base shear can be calculated under the same joint return period of the wave height and wind speed. The results show that the proposed joint probability models constructed by bivariate copulas result in lower the design environmental parameters because of the consideration of correlation between random variables. Eventually the investment cost of marginal oil fields could be relatively reduced.
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Reports on the topic "Marginal parameters"

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Kurozumi, Takushi, Ryohei Oishi, and Willem Van Zandweghe. Sticky Information Versus Sticky Prices Revisited: A Bayesian VAR-GMM Approach. Federal Reserve Bank of Cleveland, November 2022. http://dx.doi.org/10.26509/frbc-wp-202234.

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Several Phillips curves based on sticky information and sticky prices are estimated and compared using Bayesian VAR-GMM. This method derives expectations in each Phillips curve from a VAR and estimates the Phillips curve parameters and the VAR coefficients simultaneously. Quasi-marginal likelihood-based model comparison selects a dual stickiness Phillips curve in which, each period, some prices remain unchanged, consistent with micro evidence. Moreover, sticky information is a more plausible source of inflation inertia in the Phillips curve than other sources proposed in previous studies. Sticky information, sticky prices, and unchanged prices in each period are all needed to better describe inflation dynamics.
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Nadal-Caraballo, Norberto C., Madison C. Yawn, Luke A. Aucoin, Meredith L. Carr, Jeffrey A. Melby, Efrain Ramos-Santiago, Victor M. Gonzalez, et al. Coastal Hazards System–Louisiana (CHS-LA). US Army Engineer Research and Development Center, August 2022. http://dx.doi.org/10.21079/11681/45286.

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The US Army Engineer Research and Development Center (ERDC), Coastal and Hydraulics Laboratory (CHL) expanded the Coastal Hazards System (CHS) to quantify storm surge and wave hazards for coastal Louisiana. The CHS Louisiana (CHS-LA) coastal study was sponsored by the Louisiana Coastal Protection and Restoration Authority (CPRA) and the New Orleans District (MVN), US Army Corps of Engineers (USACE) to support Louisiana’s critical coastal infrastructure and to ensure the effectiveness of coastal storm risk management projects. The CHS-LA applied the CHS Probabilistic Coastal Hazard Analysis (PCHA) framework to quantify tropical cyclone (TC) responses, leveraging new atmospheric and hydrodynamic numerical model simulations of synthetic TCs developed explicitly for the Louisiana region. This report focuses on documenting the PCHA conducted for the CHS-LA, including details related to the characterization of storm climate, storm sampling, storm recurrence rate estimation, marginal distributions, correlation and dependence structure of TC atmospheric-forcing parameters, development of augmented storm suites, and assignment of discrete storm weights to the synthetic TCs. As part of CHS-LA, coastal hazards were estimated within the study area for annual exceedance frequencies (AEFs) over the range of 10 yr-1 to 1×10-4 yr-1.
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Nadal-Caraballo, Norberto, Madison Yawn, Luke Aucoin, Meredith Carr, Jeffrey Melby, Efrain Ramos-Santiago, Fabian Garcia-Moreno, et al. Coastal Hazards System–Puerto Rico and US Virgin Islands (CHS-PR). Engineer Research and Development Center (U.S.), December 2022. http://dx.doi.org/10.21079/11681/46200.

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The South Atlantic Coastal Study (SACS) was completed by the US Army Corps of Engineers to quantify storm surge and wave hazards allowing for the expansion of the Coastal Hazards System (CHS) to the South Atlantic Division (SAD) domain. The goal of the CHS-SACS was to quantify coastal storm hazards for present conditions and future sea level rise (SLR) scenarios to aid in reducing flooding risk and increasing resiliency in coastal environments. CHS-SACS was completed for three regions within the SAD domain, and this report focuses on the Coastal Hazards System–Puerto Rico and US Virgin Islands (CHS-PR). This study applied the CHS Probabilistic Coastal Hazard Analysis (PCHA) framework for quantifying tropical cyclone (TC) responses, leveraging new atmospheric and hydrodynamic numerical model simulations of synthetic TCs developed explicitly for the CHS-PR region. This report focuses on documenting the PCHA conducted for CHS-PR, including the characterization of storm climate, storm sampling, storm recurrence rate estimation, marginal distributions, correlation and dependence structure of TC atmospheric-forcing parameters, development of augmented storm suites, and assignment of discrete storm weights to the synthetic TCs. As part of CHS-PR, coastal hazards were estimated for annual exceedance frequencies over the range of 10 yr⁻¹ to 10⁻⁴ yr⁻¹.
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Ungar, Eugene D., Montague W. Demment, Uri M. Peiper, Emilio A. Laca, and Mario Gutman. The Prediction of Daily Intake in Grazing Cattle Using Methodologies, Models and Experiments that Integrate Pasture Structure and Ingestive Behavior. United States Department of Agriculture, July 1994. http://dx.doi.org/10.32747/1994.7568789.bard.

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This project addressed the prediction of daily intake in grazing cattle using methodologies, models and experiments that integrate pasture structure and ingestive behavior. The broad objective was to develop concepts of optimal foraging that predicted ingestive behavior and instantaneous intake rate in single and multi-patch environments and extend them to the greater scales of time and space required to predict daily intake. Specific objectives included: to determine how sward structure affects the shape of patch depletion curves, to determine if the basic components of ingestive behavior of animals in groups differs from animals alone, and to evaluate and modify our existing models of foraging behavior and heterogeneity to incorporate larger scales of time and space. Patch depletion was found to be predominantly by horizon, with a significant decline in bite weight during horizon depletion. This decline derives from bite overlap, and is more pronounced on taller swards. These results were successfully predicted by a simple bite placement simulator. At greater spatial scales, patch selection was aimed at maximizing daily digestible intake, with the between patch search pattern being non-random. The processes of selecting a feeding station and foraging at a feeding station are fundamentally different. The marginal value theorem may not be the most appropriate paradigm for predicting residence time at a feeding station. Basic components of ingestive behavior were unaffected by the presence of other animals. Our results contribute to animal production systems by improving our understanding of the foraging process, by identifying the key sward parameters that determine intake rate and by improving existing conceptual and quantitative models of foraging behavior across spatial and temporal scales.
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Gilmore, Walter E., Benjamin H. Sims, Mark O. Mundt, and David H. Jr Collins. The Effects of Electrostatic Discharge Phenomena on Detonator Response: A Framework for Evaluating Parameters Relevant to Quantification of Margins and Uncertainties. Office of Scientific and Technical Information (OSTI), December 2012. http://dx.doi.org/10.2172/1057601.

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Reimers, C. E. Variability of carbon system parameters in coastal waters of the Mid-Atlantic Bight off New Jersey: A link to the Ocean Margins Program. Final technical report. Office of Scientific and Technical Information (OSTI), December 1997. http://dx.doi.org/10.2172/764618.

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Siregar, Moammar Andar Roemare, Andika Afriansyah, Hendy Mirza, Doddy Hami Seno, Nugroho Purnomo, and Stefanus Purnomo. Transperitoneal versus Extraperitoneal approach for laparoscopic and robot assisted radical prostatectomy: a systematic review and meta analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, November 2022. http://dx.doi.org/10.37766/inplasy2022.11.0042.

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Review question / Objective: This study aims to compare the outcomes parameter of transperitoneal radical prostatectomy (TP-RP) vs extraperitoneal radical prostatectomy (EP-RP) approach used in Laparoscopy radical prostatectomy (LRP) or Robot-assisted radical prostatectomy (RARP). Condition being studied: Patients with history of Radical Prostatectomy using Transperitoneal Radical Prostatectomy or Extraperitoneal Radical Prostatectomy approach with Laparoscopy or Robot-Asssited surgery methods. Eligibility criteria: Studies were included if: (a) Patients have a history of Radical Prostatectomy using Laparoscopy or Robot Assisted Laparoscopy; (b) Study comparing transperitoneal vs extraperitoneal approach; (c) Original research articles (d) Outcome (Hospital stay, estimated blood loss, surgical complication, operative duration and positive surgical margin) as outcome were reported. Studies were excluded if: (a) Non comparative studies; (b) Full text not available; (c) Outcomes were not separately reported. (d) Studies before 2002.
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Farahbod, A. M., and J. F. Cassidy. Temporal variations in coda Q before and after the 2017 Barrow Strait earthquake (Mw 5.9) in Nunavut and the 2012 Haida Gwaii earthquake (Mw 7.8) in British Columbia. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/331095.

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In this study, we examine potential temporal changes in coda Q values for two significant Canadian earthquakes in different tectonic environments: the 2017 (Mw 5.9) Barrow Strait earthquake along Canada's northern margin and the 2012 (Mw 7.8) Haida Gwaii subduction earthquake on Canada's west coast. Waveforms from 124 earthquakes (2.0 &amp;lt;/= M &amp;lt;/= 4.6) for ~30 years prior to the January 8, 2017 Barrow Strait earthquake and 66 events (mainly aftershocks of M 2.0-5.3) in about 4 years after the mainshock recorded by the closest seismic station (RES) of the Canadian National Seismograph Network (CNSN) were utilized in this study. Based on our analysis, overall average of Q0 (Q at 1 Hz) decreased from 92 (before the mainshock) to 81. The most significant decrease in the frequency range between 2 and 16 Hz is observed for areas corresponding to ellipse parameter a2 of 50, 70 and 80 mainly related to aftershock activity. Precursory Q changes could not be evaluated before the mainshock due to the lack of reported seismicity within 100 km of the recording seismic station for almost 2 years from April 2015 to January 2017. Coda Q values before and after the October 28, 2012 Haida Gwaii earthquake in British Columbia show a similar pattern. Waveforms from 249 earthquakes (2.0 &amp;lt;/= M &amp;lt;/= 4.9) in 2 years before the mainshock and 498 events (2.5 &amp;lt;/= M &amp;lt;/= 6.3) in 2 years after the mainshock recorded by the three closest seismic stations of the CNSN were utilized. Overall average of Q0 decreased from 89 (before the mainshock) to 69 (station BNB), from 90 to 79 (station DIB) and from 86 to 78 (station VIB). In general, these results are in agreement with other global studies that show a decrease in Q0 following a major earthquake, likely the result of increased fracturing and fluids in the epicentral region.
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