986 resultados para spherically invariant random process
Resumo:
Most methods for small-area estimation are based on composite estimators derived from design- or model-based methods. A composite estimator is a linear combination of a direct and an indirect estimator with weights that usually depend on unknown parameters which need to be estimated. Although model-based small-area estimators are usually based on random-effects models, the assumption of fixed effects is at face value more appropriate.Model-based estimators are justified by the assumption of random (interchangeable) area effects; in practice, however, areas are not interchangeable. In the present paper we empirically assess the quality of several small-area estimators in the setting in which the area effects are treated as fixed. We consider two settings: one that draws samples from a theoretical population, and another that draws samples from an empirical population of a labor force register maintained by the National Institute of Social Security (NISS) of Catalonia. We distinguish two types of composite estimators: a) those that use weights that involve area specific estimates of bias and variance; and, b) those that use weights that involve a common variance and a common squared bias estimate for all the areas. We assess their precision and discuss alternatives to optimizing composite estimation in applications.
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We present an exact test for whether two random variables that have known bounds on their support are negatively correlated. The alternative hypothesis is that they are not negatively correlated. No assumptions are made on the underlying distributions. We show by example that the Spearman rank correlation test as the competing exact test of correlation in nonparametric settings rests on an additional assumption on the data generating process without which it is not valid as a test for correlation.We then show how to test for the significance of the slope in a linear regression analysis that invovles a single independent variable and where outcomes of the dependent variable belong to a known bounded set.
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We propose a novel compressed sensing technique to accelerate the magnetic resonance imaging (MRI) acquisition process. The method, coined spread spectrum MRI or simply s(2)MRI, consists of premodulating the signal of interest by a linear chirp before random k-space under-sampling, and then reconstructing the signal with nonlinear algorithms that promote sparsity. The effectiveness of the procedure is theoretically underpinned by the optimization of the coherence between the sparsity and sensing bases. The proposed technique is thoroughly studied by means of numerical simulations, as well as phantom and in vivo experiments on a 7T scanner. Our results suggest that s(2)MRI performs better than state-of-the-art variable density k-space under-sampling approaches.
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Sarcosaprophagous macroinvertebrates (earthworms, termites and a number of Diptera larvae) enhance changes in the physical and chemical properties of organic matter during degradation and stabilization processes in composting, causing a decrease in the molecular weights of compounds. This activity makes these organisms excellent recyclers of organic matter. This article evaluates the succession of insects associated with the decomposition of solid urban waste separated at the source. The study was carried out in the city of Medellin, Colombia. A total of 11,732 individuals were determined, belonging to the classes Insecta and Arachnida. Species of three orders of Insecta were identified, Diptera, Coleoptera and Hymenoptera. Diptera corresponding to 98.5% of the total, was the most abundant and diverse group, with 16 families (Calliphoridae, Drosophilidae, Psychodidae, Fanniidae, Muscidae, Milichiidae, Ulidiidae, Scatopsidae, Sepsidae, Sphaeroceridae, Heleomyzidae, Stratiomyidae, Syrphidae, Phoridae, Tephritidae and Curtonotidae) followed by Coleoptera with five families (Carabidae, Staphylinidae, Ptiliidae, Hydrophilidae and Phalacaridae). Three stages were observed during the composting process, allowing species associated with each stage to be identified. Other species were also present throughout the whole process. In terms of number of species, Diptera was the most important group observed, particularly Ornidia obesa, considered a highly invasive species, and Hermetia illuscens, both reported as beneficial for decomposition of organic matter.
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I study a repeated buyer-seller relationship for the exchange of a givengood. Asymmetric information over the buyer's reservation price, which issubject to random shocks, may lead the seller to use a rigid pricing policydespite the possibility of making higher profits through price discriminationacross the different satates of the buyer's reservation price. The existence of a flexible price subgame perfect equilibrium is shown for the buyerssufficiently locked-in. When the seller faces a population of buyers whose degree of involvmentin the relatioship is unknown, the flexible price equilibrium is notnecessarily optimal. Thus tipically the seller will prefer to use therigid price strategy. A learning process allowing the seller to screenthe population of buyers is derived abd the existence of a switching pointbetween the two regimes (i.e. price rigidity and price felxibility) isshown.
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This paper argues that any specific utility or disutility for gamblingmust be excluded from expected utility because such a theory is consequentialwhile a pleasure or displeasure for gambling is a matter of process, notof consequences. A (dis)utility for gambling is modeled as a process utilitywhich monotonically combines with expected utility restricted to consequences.This allows for a process (dis)utility for gambling to be revealed. Asan illustration, the model shows how empirical observations in the Allaisparadox can reveal a process disutility of gambling. A more general modelof rational behavior combining processes and consequences is then proposedand discussed.
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The examinations taken by high-school graduates in Spain and the role ofthe examination in the university admissions process are described. Thefollowing issues arising in the assessment of the process are discussed:reliability of grading, comparability of the grades and scores(equating),maintenance of standards, and compilation and use of the grading process,and their integration in the operational grading are proposed. Variousschemes for score adjustment are reviewed and feasibility of theirimplementation discussed. The advantages of pretesting of items and ofempirical checks of experts' judgements are pointed out. The paperconcludes with an outline of a planned reorganisation of the highereducation in Spain, and with a call for a comprehensive programme ofempirical research concurrent with the operation of the examination andscoring system.
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Mating can affect female immunity in multiple ways. On the one hand, the immune system may be activated by pathogens transmitted during mating, sperm and seminal proteins, or wounds inflicted by males. On the other hand, immune defences may also be down-regulated to reallocate resources to reproduction. Ants are interesting models to study post-mating immune regulation because queens mate early in life, store sperm for many years, and use it until their death many years later, while males typically die after mating. This long-term commitment between queens and their mates limits the opportunity for sexual conflict but raises the new constraint of long-term sperm survival. In this study, we examine experimentally the effect of mating on immunity in wood ant queens. Specifically, we compared the phenoloxidase and antibacterial activities of mated and virgin Formica paralugubris queens. Queens had reduced levels of active phenoloxidase after mating, but elevated antibacterial activity 7 days after mating. These results indicate that the process of mating, dealation and ovary activation triggers dynamic patterns of immune regulation in ant queens that probably reflect functional responses to mating and pathogen exposure that are independent of sexual conflict.
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This paper presents a new framework for studying irreversible (dis)investment whena market follows a random number of random-length cycles (such as a high-tech productmarket). It is assumed that a firm facing such market evolution is always unsure aboutwhether the current cycle is the last one, although it can update its beliefs about theprobability of facing a permanent decline by observing that no further growth phasearrives. We show that the existence of regime shifts in fluctuating markets suffices for anoption value of waiting to (dis)invest to arise, and we provide a marginal interpretationof the optimal (dis)investment policies, absent in the real options literature. Thepaper also shows that, despite the stochastic process of the underlying variable has acontinuous sample path, the discreteness in the regime changes implies that the samplepath of the firm s value experiences jumps whenever the regime switches all of a sudden,irrespective of whether the firm is active or not.
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This paper proposes a common and tractable framework for analyzingdifferent definitions of fixed and random effects in a contant-slopevariable-intercept model. It is shown that, regardless of whethereffects (i) are treated as parameters or as an error term, (ii) areestimated in different stages of a hierarchical model, or whether (iii)correlation between effects and regressors is allowed, when the sameinformation on effects is introduced into all estimation methods, theresulting slope estimator is also the same across methods. If differentmethods produce different results, it is ultimately because differentinformation is being used for each methods.
Resumo:
Summary points: - The bias introduced by random measurement error will be different depending on whether the error is in an exposure variable (risk factor) or outcome variable (disease) - Random measurement error in an exposure variable will bias the estimates of regression slope coefficients towards the null - Random measurement error in an outcome variable will instead increase the standard error of the estimates and widen the corresponding confidence intervals, making results less likely to be statistically significant - Increasing sample size will help minimise the impact of measurement error in an outcome variable but will only make estimates more precisely wrong when the error is in an exposure variable
Adapting the Process Writing Approach to English Language Learners with Special Needs: Using Visuals
Resumo:
The available literature on the writing characteristics and best practices to teach writing to English Language Learners who also present some disability is scarce. In order to understand and provide some insight on the developments in this field, I propose an adaptation of the Process Writing Approach based on a literature review of the existing bibliography about the writing characteristics of English Language Learners, Special Needs Learners, and English Language Learners with Special Needs’ writing, the effects of the Process Writing Approach in teaching writing to these groups, and the use of visuals in writing instruction. The main assumptions of this study are: a) The Process Writing Approach provides an opportunity to differentiate instruction to ELLs with special needs and gives them additional opportunities to bring their funds of knowledge to the classroom, improving their writing, and b) By allowing students to rely on visuals in different phases of the writing process teachers will be addressing the needs of both visual and verbal learners, therefore allowing students more options to develop writing skills. The main pedagogical implication is that by dividing writing in recursive stages and inserting visuals as scaffolding throughout the entire writing process, teachers will provide an alternative approach to writing instruction that may be more effective to English Language Learners with Special Needs.
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Recently, several anonymization algorithms have appeared for privacy preservation on graphs. Some of them are based on random-ization techniques and on k-anonymity concepts. We can use both of them to obtain an anonymized graph with a given k-anonymity value. In this paper we compare algorithms based on both techniques in orderto obtain an anonymized graph with a desired k-anonymity value. We want to analyze the complexity of these methods to generate anonymized graphs and the quality of the resulting graphs.
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Accomplish high quality of final products in pharmaceutical industry is a challenge that requires the control and supervision of all the manufacturing steps. This request created the necessity of developing fast and accurate analytical methods. Near infrared spectroscopy together with chemometrics, fulfill this growing demand. The high speed providing relevant information and the versatility of its application to different types of samples lead these combined techniques as one of the most appropriated. This study is focused on the development of a calibration model able to determine amounts of API from industrial granulates using NIR, chemometrics and process spectra methodology.