Academic literature on the topic 'Spatial autoregressions, Hypothesis testing'
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Journal articles on the topic "Spatial autoregressions, Hypothesis testing"
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Robinson, Peter M., and Francesca Rossi. "REFINED TESTS FOR SPATIAL CORRELATION." Econometric Theory 31, no. 6 (November 4, 2014): 1249–80. http://dx.doi.org/10.1017/s0266466614000498.
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We consider testing the null hypothesis of no spatial correlation against the alternative of pure first order spatial autoregression. A test statistic based on the least squares estimate has good first-order asymptotic properties, but these may not be relevant in small- or moderate-sized samples, especially as (depending on properties of the spatial weight matrix) the usual parametric rate of convergence may not be attained. We thus develop tests with more accurate size properties, by means of Edgeworth expansions and the bootstrap. Although the least squares estimate is inconsistent for the correlation parameter, we show that under quite general conditions its probability limit has the correct sign, and that least squares testing is consistent; we also establish asymptotic local power properties. The finite-sample performance of our tests is compared with others in Monte Carlo simulations.
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Cavaliere, Giuseppe, and Iliyan Georgiev. "EXPLOITING INFINITE VARIANCE THROUGH DUMMY VARIABLES IN NONSTATIONARY AUTOREGRESSIONS." Econometric Theory 29, no. 6 (August 13, 2013): 1162–95. http://dx.doi.org/10.1017/s0266466613000030.
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We consider estimation and testing in finite-order autoregressive models with a (near) unit root and infinite-variance innovations. We study the asymptotic properties of estimators obtained by dummying out “large” innovations, i.e., those exceeding a given threshold. These estimators reflect the common practice of dealing with large residuals by including impulse dummies in the estimated regression. Iterative versions of the dummy-variable estimator are also discussed. We provide conditions on the preliminary parameter estimator and on the threshold that ensure that (i) the dummy-based estimator is consistent at higher rates than the ordinary least squares estimator, (ii) an asymptotically normal test statistic for the unit root hypothesis can be derived, and (iii) order of magnitude gains of local power are obtained.
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Shen, Xiaotong, Hsin-Cheng Huang, and Noel Cressie. "Nonparametric Hypothesis Testing for a Spatial Signal." Journal of the American Statistical Association 97, no. 460 (December 2002): 1122–40. http://dx.doi.org/10.1198/016214502388618933.
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Schneider, Darryl W. "Alertness and cognitive control: Testing the spatial grouping hypothesis." Attention, Perception, & Psychophysics 81, no. 6 (May 23, 2019): 1913–25. http://dx.doi.org/10.3758/s13414-019-01764-x.
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Mur, Jesús, Fernando López, and Ana Angulo. "Testing the hypothesis of stability in spatial econometric models." Papers in Regional Science 88, no. 2 (June 2009): 409–44. http://dx.doi.org/10.1111/j.1435-5957.2009.00224.x.
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Nedimović, Predrag, and Sučica Zdravković. "Lightness contrast & assimilation: testing the hypotheses." Primenjena psihologija 14, no. 3 (November 17, 2021): 253–75. http://dx.doi.org/10.19090/pp.2021.3.253-275.
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Lightness contrast alters lightness of a target decreasing its similarity with neighbouring surfaces (inducers), while lightness assimilation has an opposite effect, similarity is increased. Previous studies emphasized some aspects of stimulation that favour occurrence of one or both of these two phenomena: spatial frequency of the inducers, magnitude and direction of the reflectance difference between the target and the inducers. More importantly, based on previous studies three precise hypotheses can be formulated that predict occurrence of the two phenomena: spatial frequency, differential stimulation and assimilation asymmetry.
We manipulated target and inducers’ reflectance, and inducers’ spatial frequency. This enabled us not only to test the importance of these factors, but to predict lightness for each stimulus, according to all three hypotheses. Our results confirmed the importance of tested factors for both lightness contrast and assimilation.
Unfortunately, the proposed hypotheses were poor in predicting the obtained data. Differential stimulation hypothesis correctly predicted obtained effect in less than half situations, since small reflectance differences produced contrast, and large differences produced assimilation. Spatial frequency hypothesis did not correctly predict the strength of obtained effects, and we obtained largest assimilation effects with low spatial frequency inducers. Finally, assimilation asymmetry hypothesis did not predict a single obtained effect. Contrary to this hypothesis predictions, we obtained contrast with decrement, and assimilation with increment inducers.
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Weidner, R., N. J. Shah, and G. R. Fink. "The Neural Basis of Perceptual Hypothesis Generation and Testing." Journal of Cognitive Neuroscience 18, no. 2 (February 1, 2006): 258–66. http://dx.doi.org/10.1162/jocn.2006.18.2.258.
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Four-dot masking is a new form of visual masking that does not involve local contour interactions or spatial superimposition of the target stimulus and the mask (as, e.g., in pattern or metacontrast masking). Rather, the effective masking mechanism is based on object substitution. Object substitution masking occurs when low-level visual information representations are altered before target identification through iterative interaction with high-level visual processing stages has been completed. Interestingly, object substitution interacts with attention processes: Strong masking effects are observed when attentional orientation toward the target location is delayed. In contrast, no masking occurs when attention can be rapidly shifted to and engaged onto the target location. We investigated the neural basis of object substitution masking by studying the interaction of spatial attention and masking processes using functional magnetic resonance imaging. Behavioral data indicated a two-way interaction between the factors Spatial Attention (valid vs. invalid cueing) and Masking (four-dot vs. pattern masking). As expected, spatial attention improved performance more strongly during object substitution masking. Functional correlates of this interaction were found in the primary visual cortex, higher visual areas, and left intraparietal sulcus. A region-of-interest analysis in these areas revealed that the largest blood oxygenation level-dependent signal changes occurred during effective four-dot masking. In contrast, the weakest signal changes in these areas were observed when target visibility was highest. The data suggest that these areas represent an object substitution network dedicated to the generation and testing of a perceptual hypotheses as described by the object substitution theory of masking of Di-Lollo et al. [Competition for consciousness among visual events: The psychophysics of reentrant visual processes. Journal of Experimental Psychology: General, 129, 481–507, 2000].
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Meilán-Vila, Andrea, Jean Opsomer, Mario Francisco-Fernández, and Rosa Crujeiras. "Testing Goodness-of-Fit of Parametric Spatial Trends." Proceedings 2, no. 18 (September 17, 2018): 1185. http://dx.doi.org/10.3390/proceedings2181185.
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The aim of this work is to propose and analyze the behavior of a test statistic to assess a parametric trend surface, that is, a regression model with spatially correlated errors. The asymptotic behavior under the null hypothesis, as well as the asymptotic power of the test under local alternatives will be analyzed. Finite sample performance of the test is addressed by simulation, introducing a bootstrap calibration procedure.
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Muelenz, Cornelius, Matthias Gamer, and Heiko Hecht. "Testing the Egocentric Mirror-Rotation Hypothesis." Seeing and Perceiving 23, no. 5 (2010): 373–83. http://dx.doi.org/10.1163/187847510x540000.
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AbstractAlthough observers know about the law of reflection, their intuitive understanding of spatial locations in mirrors is often erroneous. Hecht et al. (2005) proposed a two-stage mirror-rotation hypothesis to explain these misconceptions. The hypothesis involves an egocentric bias to the effect that observers behave as if the mirror surface were rotated by about 2° to be more orthogonal than is the case. We test four variants of the hypothesis, which differ depending on whether the virtual world, the mirror, or both are taken to be rotated. We devised an experimental setup that allowed us to distinguish between these variants. Our results confirm that the virtual world — and only the virtual world — is being rotated. Observers had to perform a localization task, using a mirror that was either fronto-parallel or rotated opposite the direction of the predicted effect. We were thus able to compensate for the effect. The positions of objects in mirrors were perceived in accordance with the erroneous conception that the virtual world behind the mirror is slightly rotated and that the reconstruction is based on the non-rotated fronto-parallel mirror. A covert rotation of the mirror by about 2° against the predicted effect was able to compensate for the placement error.
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Guarte, Jacqueline, and Erniel Barrios. "Nonparametric Hypothesis Testing in a Spatial-Temporal Model: A Simulation Study." Communications in Statistics - Simulation and Computation 42, no. 1 (January 2013): 153–70. http://dx.doi.org/10.1080/03610918.2011.633725.
Full textDissertations / Theses on the topic "Spatial autoregressions, Hypothesis testing"
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ROSSI, FRANCESCA. "Inference for spatial data." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2011. http://hdl.handle.net/10281/25536.
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It is well known that econometric modelling and statistical inference are considerably complicated by the possibility of correlation across data data recorded at different locations in space. A major branch of the spatial econometrics literature has focused on testing the null hypothesis of spatial independence in Spatial Autoregressions (SAR) and the asymptotic properties of standard test statistics have been widely considered. However, finite sample properties of such tests have received relatively little consideration. Indeed, spatial datasets are likely to be small or moderately-sized and thus the derivation of finite sample corrections appears to be a crucially important task in order to obtain reliable tests. In this project we consider finite sample corrections based on formal Edgeworth expansions for the cumulative distribution function of some relevant test statistics.
In Chapters 1 and 2 we present refined procedures for testing nullity of the spatial parameter in pure SAR based on ordinary least squares and Gaussian maximum likelihood, respectively. In both cases, the Edgeworth-corrected tests are compared with those obtained by a bootstrap procedure, which is supposed to have similar properties. The practical performance of new tests is assessed with Monte Carlo simulations and two empirical examples. In Chapter 3 we propose finite sample corrections for Lagrange Multiplier statistics, which are computationally particularly convenient as the estimation of the spatial parameter is not required. Monte Carlo simulations and the numerical implementation of Imhof's procedure confirm that the corrected tests outperform standard ones.
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Kibler, Robyn M. "Testing the Medical Arms Race Hypothesis: a Spatial Approach." Scholar Commons, 2017. http://scholarcommons.usf.edu/etd/6879.
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The surgical robot experienced rapid uptake throughout hospitals in the US despite lack of clinical evidence that it is superior to existing methods and undeterred by its high cost. This type of technology may be a “weapon” in the medical arms race hypothesis which asserts that competition among hospitals may be welfare reducing wherein it encourages resource use that is not commensurate with beneficial health outcomes. This paper is a case-study of the diffusion of the surgical robot among hospitals in Florida. We address the medical arms race hypothesis directly by investigating whether a hospital’s decision to adopt a robot is a function of the neighboring, competing hospitals’ decisions to do so. Using a spatial autoregressive probit model, we find that the spatial coefficient is significant and negative. That is, when neighboring hospitals operate a robot, a given hospital is less likely to operate one. Indeed, hospitals appear to consider the behavior of rival hospitals, but not in a way that would be consistent with a medical arms race. Support is lent to the hypothesis that as more hospitals become providers of robotic-assisted surgery, the less profitable it becomes to enter the market.
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Ferraccioli, Federico. "Nonparametric methods for complex spatial domains: density estimation and hypothesis testing." Doctoral thesis, Università degli studi di Padova, 2020. http://hdl.handle.net/11577/3424887.
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The analysis of not only big, but increasingly complex data represents a thriving branch of statistics. Modern applications ranging from neuroscience, geo-sciences, astronomy and engineering pose stimulating challenges to classical statistics and require the development of novel methodologies. In this thesis we propose nonparametric approaches to density estimation and hypothesis testing over multidimensional domains with complex shapes. The synergy of ideas and techniques from applied mathematics, numerical analysis and statistics allows us to obtain flexible and efficient tools. The thesis is organized in three main threads. The first considers the problem of density estimation over multidimensional domains with complex shapes. Here we combine a nonparametric likelihood approach with a regularization involving partial differential operators. The second thread examines two sample hypothesis testing. Inspired by the first part, we take advantage of permutation procedures to develop high dimensional
multinomial tests for distributions defined over complex domain. The last thread moves toward a parallel direction, that is the study of hypothesis testing procedures for semiparametric spatial regression models. After a careful analysis of their theoretical properties, we propose a nonparametric randomization approach to test the linear
components of such models.
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Houston, Donald Sinclair. "Spatial barriers to employment within metropolitan areas : testing the spatial mismatch hypothesis using evidence from firm relocations in the Glasgow conurbation." Thesis, University of Glasgow, 2001. http://theses.gla.ac.uk/4357/.
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This thesis applies the spatial mismatch hypothesis to the Glasgow conurbation in Britain. It also develops an innovative methodology which addresses some of the methodological concerns associated with much previous work and allows three different types of spatial barrier to employment to be examined - commuting, residential mobility and job search / recruitment. Specifically, this thesis looks at firms which have relocated within the Glasgow conurbation. The number of employees who leave their job or move house because their employer relocates is examined in order to assess to what extent commuting and residential mobility are barriers to employment within metropolitan areas. Recruitment patterns to the firm's new sites are analysed in order to assess the extent of job search and recruitment as spatial barriers to employment. The results show that those without access to a car and those in lower-paid and lower-skilled jobs are least able to commute to the new sites, and are the least able to move house closer to work, and so consequently are more likely to leave their job. Those in higher paid and more secure jobs are more likely to move house closer to work. People recruited at the new sites tend to live much closer to the firms than the remaining original workforce, which suggests that across space, job search and recruitment processes, as well as social networks and other neighbourhood effects, may be greater barriers to employment than commuting. The theoretical and policy implications of these findings are discussed. It is argued that skills and spatial mismatches reinforce each other, and that this interaction needs to be incorporated into explanations of the relative importance of each. The proximity of jobs to neighbourhoods within metropolitan areas needs to be considered in understanding the level of unemployment in small areas.
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Coppola, Vincent Jesse. "Neurocognitive aging in homing pigeons (Columba livia):Further investigation into hippocampal-dependent memory impairment and testing of the cholinergic hypothesis of cognitive decline." Bowling Green State University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1553609743315119.
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Grahl, Paulo Gustavo de Sampaio. "Essays on Spatial Econometrics." reponame:Repositório Institucional do FGV, 2012. http://hdl.handle.net/10438/11268.
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Esta dissertação concentra-se nos processos estocásticos espaciais definidos em um reticulado, os chamados modelos do tipo Cliff & Ord. Minha contribuição nesta tese consiste em utilizar aproximações de Edgeworth e saddlepoint para investigar as propriedades em amostras finitas do teste para detectar a presença de dependência espacial em modelos SAR (autoregressivo espacial), e propor uma nova classe de modelos econométricos espaciais na qual os parâmetros que afetam a estrutura da média são distintos dos parâmetros presentes na estrutura da variância do processo. Isto permite uma interpretação mais clara dos parâmetros do modelo, além de generalizar uma proposta de taxonomia feita por Anselin (2003). Eu proponho um estimador para os parâmetros do modelo e derivo a distribuição assintótica do estimador. O modelo sugerido na dissertação fornece uma interpretação interessante ao modelo SARAR, bastante comum na literatura. A investigação das propriedades em amostras finitas dos testes expande com relação a literatura permitindo que a matriz de vizinhança do processo espacial seja uma função não-linear do parâmetro de dependência espacial. A utilização de aproximações ao invés de simulações (mais comum na literatura), permite uma maneira fácil de comparar as propriedades dos testes com diferentes matrizes de vizinhança e corrigir o tamanho ao comparar a potência dos testes. Eu obtenho teste invariante ótimo que é também localmente uniformemente mais potente (LUMPI). Construo o envelope de potência para o teste LUMPI e mostro que ele é virtualmente UMP, pois a potência do teste está muito próxima ao envelope (considerando as estruturas espaciais definidas na dissertação). Eu sugiro um procedimento prático para construir um teste que tem boa potência em uma gama de situações onde talvez o teste LUMPI não tenha boas propriedades. Eu concluo que a potência do teste aumenta com o tamanho da amostra e com o parâmetro de dependência espacial (o que está de acordo com a literatura). Entretanto, disputo a visão consensual que a potência do teste diminui a medida que a matriz de vizinhança fica mais densa. Isto reflete um erro de medida comum na literatura, pois a distância estatística entre a hipótese nula e a alternativa varia muito com a estrutura da matriz. Fazendo a correção, concluo que a potência do teste aumenta com a distância da alternativa à nula, como esperado.
This dissertation focus on spatial stochastic process on a lattice (Cliff & Ord--type of models). My contribution consists of using Edgeworth and saddlepoint series to investigate small sample size and power properties of tests for detecting spatial dependence in spatial autoregressive (SAR) stochastic processes, and proposing a new class of spatial econometric models where the spatial dependence parameters that enter the mean structure are different from the ones in the covariance structure. This allows a clearer interpretation of models' parameters and generalizes the set of local and global models suggested by Anselin (2003) as an alternative to the traditional Cliff & Ord models. I propose an estimation procedure for the model's parameters and derive the asymptotic distribution of the parameters' estimators. The suggested model provides some insights on the structure of the commonly used mixed regressive, spatial autoregressive model with spatial autoregressive disturbances (SARAR). The study of the small sample properties of tests to detect spatial dependence expands on the existing literature by allowing the neighborhood structure to be a nonlinear function of the spatial dependence parameter. The use of series approximations instead of the often used Monte Carlo simulation allows a simple way to compare test properties across different neighborhood structures and to correct for size when comparing power. I obtain the power envelope for testing the presence of spatial dependence in the SAR process using the optimal invariant test statistic, which is also locally uniformly most powerful invariant (LUMPI). I have found that the LUMPI test is virtually UMP since its power is very close to the power envelope. I suggest a practical procedure to build a test that, while not UMP, retain good power properties in a wider range for the spatial parameter when compared to the LUMPI test. I find that power increases with sample size and with the spatial dependence parameter -- which agrees with the literature. However, I call into question the consensus view that power decreases as the spatial weight matrix becomes more densely connected. This finding in the literature reflects an error of measure because the hypothesis being compared are at very different statistical distance from the null. After adjusting for this, the power is larger for alternative hypothesis further away from the null -- as one would expect.
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Akgun, Oguzhan. "Dépendance inter-individuelle sur panels hétérogènes : estimation, inférence et prévision." Thesis, Paris 2, 2019. http://www.theses.fr/2019PA020008.
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La disponibilité de données de panel ayant des dimensions temporelle et individuelle comparables et importantes augmente rapidement. Cette structure offre de nouvelles perspectives pour appréhender et caractériser les dépendances inter-individuelles. Cette thèse, tout en s'appuyant sur la littérature récente liée aux panels hétérogènes de grande taille en présence de dépendances inter-individuelles, en propose trois prolongements. Le premier chapitre traite des problèmes d'estimation, d'inférence et de prévision, en se concentrant sur la comparaison d'estimateurs hétérogènes, homogènes et partiellement homogènes en présence de dépendances inter-individuelles. Ces dernières renvoient à des structures de dépendance spatiale sur les perturbations et à la présence de facteurs communs. Le deuxième chapitre se focalise sur l'élaboration de tests robustes à différentes structures de dépendance inter-individuelle afin d'évaluer la qualité prédictive de plusieurs panels. Enfin, le troisième chapitre se concentre sur les prévisions, obtenues sur la base d'approches itérée et directe, et l'introduction de termes spécifiques liés aux dépendances inter-individuelles dans les prédicteurs. La comparaison des prévisions de taux d'inflation sur un panel de pays de l'OCDE révèle notamment l'importance de la prise en compte des facteurs communsThe availability of panel data sets with comparable and large time and individual dimensions is rapidly increasing. This structure offers new possibilities to understand and characterize cross-sectional dependence. This thesis makes three contributions to the recent literature dealing with large heterogeneous panel data sets with cross-sectional dependence. The first chapter deals with estimation, inference and forecasting issues focusing on the comparison of heterogeneous, homogeneous and partially homogeneous panel data estimators in presence of cross-sectional dependence modeled by spatial error dependence and common factors. In the second chapter novel tests for equal predictive ability in panels of forecasts are proposed, allowing for different types and strength of cross-sectional dependence across units. Finally, the third chapter focuses on forecasts obtained using iterated and direct methods. A special emphasis is put on the predictors which contain terms related to interactions between panel units. Inflation forecasts for the OECD countries are compared empirically. The results show the importance of taking common factors into account to predict inflation
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Feindouno, Sosso. "Structural vulnerability and fragility : an assessment based on composite indicators." Thesis, Université Clermont Auvergne (2017-2020), 2018. http://www.theses.fr/2018CLFAD014.
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Les concepts de vulnérabilité et de fragilité sont au cœur du débat sur la définition et la mise en œuvre des objectifs de développement durable. Cette thèse propose des outils pour évaluer la vulnérabilité structurelle et la fragilité sous divers aspects: économique, social et environnemental. L'approche proposée pour appréhender ces concepts repose sur la construction et le raffinement d'indicateurs composites. Elle est composée de quatre chapitres.Dans le Chapitre 1, nous construisons des séries rétrospectives de l’indice de vulnérabilité économique (EVI) proposé par le Comité des politiques de développement des Nations Unies pour l’identification des Pays les Moins Avancés (PMA). La vulnérabilité économique structurelle des PMA reste supérieure à celle des non-PMA. De plus, en se focalisant sur le cadre africain, nous montrons que les Etats fragiles sont économiquement plus vulnérables que les Etats non fragiles et que, la différence entre les deux groupes de pays est essentiellement due à l’ampleur des chocs. Enfin, en utilisant une approche basée sur la stochastique dominance et un horizon temporel de cinq ans, nous observons qu’il n’y a pas de baisse significative de l’EVI et de ses principaux composants au premier ordre. En revanche, une diminution généralisée peut être conclue au second ordre.Le Chapitre 2 est consacré à la question de la résilience structurelle à travers un indice de capital humain (HAI). Nous présentons les séries rétrospectives du HAI et de ses composants, pour lesquels des outils économétriques ont été utilisés pour imputer les données manquantes. Nous analysons la dynamique du HAI en évaluant la contribution de chacun de ses composants. Enfin, nous débattons de la problématique cruciale de la pondération et proposons un nouveau système de poids basé sur le rapport de corrélation et la linéarité (ou non linéarité) entre les composants.Le Chapitre 3 a trait à la vulnérabilité au changement climatique. Après avoir mis en lumière le flou existant autour de la définition et de la mesure de la vulnérabilité au changement climatique, nous construisons un indice composite appelé « Physical Vulnerability to Climate Change Index (PVCCI) ». Cet indice repose uniquement sur les caractéristiques physiques du changement climatique et est indépendant des politiques présentes et futures des pays. Il a vocation à être utilisé pour l’allocation internationale des ressources. Pour finir, le Chapitre traite de la relation entre conflits civils et vulnérabilité au changement climatique, mesurée ici par le PVCCI.Le Chapitre 4 part du constat que les pays africains accusent encore un retard dans l’attraction des investissements directs étrangers (IDE). Nous soupçonnons les facteurs de vulnérabilité économique structurelle, mesurée par l’EVI, d’être en partie responsables du manque d’intérêt relatif des investisseurs étrangers à l’égard de l’Afrique. Nous estimons un modèle spatial à correction d’erreur sur la période 1980-2010 pour évaluer les relations dynamiques entre les IDE et ses déterminants. Notre analyse révèle qu’à long terme, il existe une relation négative et significative entre les IDE et l’EVI. Les résultats suggèrent également qu’un EVI élevé dans les pays voisins a un impact négatif sur les IDE du pays hôte. Pour finir, nous montrons que la vulnérabilité économique structurelle joue un rôle important dans l’explication de l’écart en termes d’IDE entre les pays africains à faible revenu et les pays africains à revenu intermédiaire. La part de l’agriculture, de la foresterie et de la pêche dans le PIB apparait comme le principal facteur contribuant à cet écartVulnerability and fragility are at the heart of the global debate arising from the definition and implementation of the sustainable development goals. This PhD dissertation offers enhanced tools to assess structural vulnerability and fragility from various aspects: economic, social, and environmental. The proposed approach for apprehending these concepts is based on the construction and refinement of composite indicators. It is divided into four chapters.In Chapter 1, we build the retrospective series of the economic vulnerability index (EVI), proposed by the United Nations’ Committee for Development Policy (CDP). Some choices and measures are discussed, such as the methodology used to calculate the instabilities of exports and agricultural production. From our analyses, it appears that the structural economic vulnerability of LDCs is still higher compared to non-LDCs. As well, focusing on the African context, we show that fragile African states are economically more vulnerable than non-fragile African states, and the difference between the two groups of countries seems to come from the difference in the magnitude of shocks. Finally, employing a stochastic dominance approach and using a five-year testing horizon to assess the evolution of the EVI and its main components over time, we observe that there is no real decline of the EVI and its main components at the first order sense. But, an overall decrease can be concluded at the second order sense of dominance.The second chapter focuses on the issue of structural resilience through the Human Assets Index (HAI), another index designed by the UN-CDP for identification of LDCs. We start with a presentation of retrospective series of the HAI and its components, for which, to a limited extend, we have used econometric tools to consistently impute missing data. Secondly, we analyze the HAI’s dynamics by assessing the contributions of each component to this. Finally, we debate about the choice of equal weighting for the four components in the HAI. Taking into account the fact that the correlation between indicators is closely linked to the issue, we propose a new scheme pattern based on the correlation ratio and linearity (or nonlinearity) dependence between components. The third chapter is devoted to the climate change vulnerability. We design a composite indicator called “Physical Vulnerability to Climate Change (PVCCI)”. This indicator based only on the physical characteristics of climate change is independent of present and future country policy, and aims to be used for international allocation of resources. After explaining the specific methodology used to build the PVCCI and presenting the results for developing countries, we investigate the relationship between civil conflict and vulnerability to climate change measured here by the PVCCI. The starting point of the fourth chapter is that African countries are still lagging behind when it comes to attracting Foreign Direct Investments (FDI). We suspect the structural economic vulnerability, measured by the Economic Vulnerability Index (EVI), in part, responsible for the relative lack of interest of foreign investors towards Africa. We estimate a spatial error correction model during the time period from 1980 to 2010 to assess the dynamic relationships between FDI and its determinants. Our finding reveals that in the long run, there is a significant negative relationship between FDI and EVI. The results also suggest that a high EVI in neighboring countries negatively affects the amount of FDI into a host country. Later on, we also observe that structural economic vulnerability plays an important role in explaining the FDI gap between African Low-Income Countries and African Middle-Income Countries. The share of agriculture, forestry and fishery in GDP appears as the strongest contributing factor to this difference
Books on the topic "Spatial autoregressions, Hypothesis testing"
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Franzese, Robert J., and Jude C. Hays. Empirical Models of Spatial Inter‐Dependence. Edited by Janet M. Box-Steffensmeier, Henry E. Brady, and David Collier. Oxford University Press, 2009. http://dx.doi.org/10.1093/oxfordhb/9780199286546.003.0025.
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This article discusses the role of ‘spatial interdependence’ between units of analysis by using a symmetric weighting matrix for the units of observation whose elements reflect the relative connectivity between unit i and unit j. It starts by addressing spatial interdependence in political science. There are two workhorse regression models in empirical spatial analysis: spatial lag and spatial error models. The article then addresses OLS estimation and specification testing under the null hypothesis of no spatial dependence. It turns to the topic of assessing spatial lag models, and a discussion of spatial error models. Moreover, it reports the calculation of spatial multipliers. Furthermore, it presents several newer applications of spatial techniques in empirical political science research: SAR models with multiple lags, SAR models for binary dependent variables, and spatio-temporal autoregressive (STAR) models for panel data.
Book chapters on the topic "Spatial autoregressions, Hypothesis testing"
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Honor, Richard, and Robert I. Colautti. "EICA 2.0: a general model of enemy release and defence in plant and animal invasions." In Plant invasions: the role of biotic interactions, 192–207. Wallingford: CABI, 2020. http://dx.doi.org/10.1079/9781789242171.0192.
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Abstract Plants and animals have evolved a variety of strategies to limit the negative fitness consequences of natural enemies (i.e. herbivores, predators, parasites and pathogens). Demographic bottlenecks occurring during the invasion process reduce the number of co-introduced natural enemies, providing opportunities to study rapid evolution in environments with different or reduced enemy loads. Enemy release theory provides a set of hypotheses and predictions about the role of natural enemies in the proliferation of invasive species. This body of theory includes the Enemy Release Hypothesis (ERH) and the related Evolution of Increased Competitive Ability Hypothesis (EICA), but there is often confusion about these hypotheses and the data needed to test them. We introduce a simple, general model of enemy release to identify and clarify some of the key assumptions and predictions implicit in enemy release theory and its impacts on invasion. Although introduced populations likely benefit from a reduction in the direct fitness impacts of natural enemies in the early stages of invasion, an evolutionary shift in resource allocation from defence to growth and reproduction is much less likely and depends on a delicate balance between the fitness costs and benefits of defence and the fitness impacts of natural enemies in both the native and introduced ranges. Even when the abundance of natural enemies is lower in the introduced range, the majority of scenarios do not favour evolution of less defended genotypes that are more competitive or more fecund, contrary to predictions of EICA. Perhaps surprisingly, we find that the level of damage by natural enemies in field surveys is not generally a good parameter for testing enemy release theory. Instead, common garden experiments characterizing fitness reaction norms of multiple genotypes from the native and introduced range are crucial to estimate the historic rate of adaptive evolution or predict it into the future. Incorporating spatial autocorrelation and methods from population genetics can further improve our understanding of the role of enemy release and evolution in the proliferation of invasive species.
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"Hypothesis testing in the presence of spatial dependence." In Spatial Data Analysis, 273–86. Cambridge University Press, 2003. http://dx.doi.org/10.1017/cbo9780511754944.010.
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Oyana, Tonny J. "Engaging in Exploratory Data Analysis, Visualization, and Hypothesis Testing." In Spatial Analysis with R, 105–42. CRC Press, 2020. http://dx.doi.org/10.1201/9781003021643-4.
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"Engaging in Exploratory Data Analysis, Visualization, and Hypothesis Testing ............................................................................................. Exploratory Data Analysis, Geovisualization, and Data." In Spatial Analysis, 106–39. CRC Press, 2015. http://dx.doi.org/10.1201/b18808-8.
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Shettleworth, Sara J., and Robert R. Hampton. "Adaptive Specializations of Spatial Cognition in Food-storing Birds? Approaches to Testing a Comparative Hypothesis." In Animal Cognition in Nature, 65–98. Elsevier, 1998. http://dx.doi.org/10.1016/b978-012077030-4/50055-6.
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Wang, Fahui, and Van O’Brien. "Constructing Geographic Areas for Analysis of Homicide in Small Populations." In Geographic Information Systems and Crime Analysis, 84–101. IGI Global, 2005. http://dx.doi.org/10.4018/978-1-59140-453-8.ch005.
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The rate estimates for rare events like homicide in small populations are very susceptible to data errors, and thus compromise the validity of inferences. This chapter discusses two geographic information systems (GIS)-based methods for constructing geographic areas with sufficiently large base populations to permit reliable estimates of homicide rates to be obtained. One is the spatial order method, and the other is the ISD method (after the Information & Statistics Division of the Health Service in Scotland, where it was devised). Both methods construct new analysis areas based on spatial proximity of basic units. For demonstration, the methods are applied to testing the herding-culture-of-honor hypothesis proposed by Nisbett and Reaves, and the result shows that the herding-culture-of-honor proposition is merely an artifact of unreliable estimate of homicide rates. The methodology, in general, is applicable to analysis of any rates with small base populations.
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Getzen, Thomas E. "Measuring NHE: Accounting, Boundaries, and Budgets." In Money and Medicine, 193—C10.N44. Oxford University PressNew York, 2023. http://dx.doi.org/10.1093/oso/9780197573266.003.0010.
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Abstract The international system of health accounts (SHA) depends on statistical constructs generated to meet the needs of government ministries. Economic analysis depends on matching the temporal and spatial boundaries of units of observation to the span of action. Here the appropriate scale for quantification and measurement is “national expenditures relative to income over decades” rather than “amounts spent by persons for an illness.” Historical and conceptual developments in accounting provide insight into use of terms such as “money,” “technology,” “growth,” “health expenditure,” and “trend,” leading toward what could be termed a “budgetary perspective.” Attempts to quantify rates of technological change demonstrate some of the limits to econometric measurement and hypothesis testing.
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Nikolova, Natalia D., Snejana Ivanova, Gergana Georgieva, Ivan Armenski, and Kiril I. Tenekedjiev. "Bootstrap Evaluation of Expert Panel Opinion in Case Studies Solved by REPOMP." In Advances in Environmental Engineering and Green Technologies, 48–76. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-8333-4.ch002.
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This chapter discusses several applications of the REPOMP procedure (Randomized Expert Panel Opinion Marginalizing Procedure). It analyzes the subjective opinion of an expert panel in a multi-criteria decision making situation. It starts with an expert panel constructing a hierarchical structure of criteria to evaluate the alternatives. At a next stage, the same expert panel evaluates the relative weight of each criterion and the degree of compliance of each alternative with those criteria. Then a randomized procedure is applied to calculate the marginal indicator of each alternative and make the final ordering based on it. Additional simulation procedure is applied to analyze the distribution of that marginal indicator. The alternatives are also being allocated to indifference classes using hypothesis testing procedures. The analyzed examples refer to issues in environmental management, energy efficiency and spatial data infrastructures.
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Honor, Richard, and Robert L. Colautti. "EICA 2.0: a general model of enemy release and defence in plant and animal invasions." In Plant invasions: the role of biotic interactions, 192–207. CABI, 2020. http://dx.doi.org/10.1079/9781789242171.0010.
Full textAbstract:
Plants and animals have evolved a variety of strategies to limit the negative fitness consequences of natural enemies (i.e. herbivores, predators, parasites and pathogens). Demographic bottlenecks occurring during the invasion process reduce the number of co-introduced natural enemies, providing opportunities to study rapid evolution in environments with different or reduced enemy loads. Enemy release theory provides a set of hypotheses and predictions about the role of natural enemies in the proliferation of invasive species. This body of theory includes the Enemy Release Hypothesis (ERH) and the related Evolution of Increased Competitive Ability Hypothesis (EICA), but there is often confusion about these hypotheses and the data needed to test them. We introduce a simple, general model of enemy release to identify and clarify some of the key assumptions and predictions implicit in enemy release theory and its impacts on invasion. Although introduced populations likely benefit from a reduction in the direct fitness impacts of natural enemies in the early stages of invasion, an evolutionary shift in resource allocation from defence to growth and reproduction is much less likely and depends on a delicate balance between the fitness costs and benefits of defence and the fitness impacts of natural enemies in both the native and introduced ranges. Even when the abundance of natural enemies is lower in the introduced range, the majority of scenarios do not favour evolution of less defended genotypes that are more competitive or more fecund, contrary to predictions of EICA. Perhaps surprisingly, we find that the level of damage by natural enemies in field surveys is not generally a good parameter for testing enemy release theory. Instead, common garden experiments characterizing fitness reaction norms of multiple genotypes from the native and introduced range are crucial to estimate the historic rate of adaptive evolution or predict it into the future. Incorporating spatial autocorrelation and methods from population genetics can further improve our understanding of the role of enemy release and evolution in the proliferation of invasive species.
Conference papers on the topic "Spatial autoregressions, Hypothesis testing"
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Golz, Martin, Michael Muma, Topi Halme, Abdelhak Zoubir, and Visa Koivunen. "Spatial Inference in Sensor Networks using Multiple Hypothesis Testing and Bayesian Clustering." In 2019 27th European Signal Processing Conference (EUSIPCO). IEEE, 2019. http://dx.doi.org/10.23919/eusipco.2019.8902986.
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Michele, Torresani, Rocchini Duccio, Zebisch Marc, Sonnenschein Ruth, and Tonon Giustino. "Testing the spectral variation hypothesis by using the RAO-Q index to estimate forest biodiversity: Effect of spatial resolution." In IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2018. http://dx.doi.org/10.1109/igarss.2018.8666630.
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Ankireddi, Sai, Henry H. Jung, and James Jones. "On the Correlation Between Power Density Distribution and Junction-Case Thermal Resistance for Electronic Packages." In ASME 2003 International Electronic Packaging Technical Conference and Exhibition. ASMEDC, 2003. http://dx.doi.org/10.1115/ipack2003-35310.
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When comparing two electronic packages identical in all respects except die plan dimensions and power, wherein the package with the smaller die is associated with a lower power, it is often hypothesized that the lower-powered package would have a lower junction-case thermal resistance. This hypothesis is generally based on the questionable argument that because the smaller package has lower power, its internal temperatures should be lower and hence a lower junction-case resistance should be ‘intuitively’ expected. In this article we show that drawing inferences about trends in junction-case resistance based merely on power trends, as outlined above, can be incorrect. In order to address this issue and provide better ‘indicators’ for comparing thermal performance across packages, we introduce the concept of the Power Density Distribution (PDD) and show how it relates with the junction-case thermal resistance. To illustrate its use in comparing thermal performance of packages we consider examples of several ICs with different die size/power combinations. Additionally, we also note the correlation between peaks in the spatial distribution of the power density and those of the die temperature distribution; in effect, this furnishes a simple way to identify candidate hot-spot locations on the die without resorting to extensive numerical thermal simulation/testing. We illustrate this intuitively anticipated concept for a variety of power distribution scenarios in some of our example IC packages.
Reports on the topic "Spatial autoregressions, Hypothesis testing"
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Nieto-Castanon, Alfonso. CONN functional connectivity toolbox (RRID:SCR_009550), Version 18. Hilbert Press, 2018. http://dx.doi.org/10.56441/hilbertpress.1818.9585.
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CONN is a Matlab-based cross-platform software for the computation, display, and analysis of functional connectivity in fMRI (fcMRI). Connectivity measures include seed-to-voxel connectivity maps, ROI-to- ROI connectivity matrices, graph properties of connectivity networks, generalized psychophysiological interaction models (gPPI), intrinsic connectivity, local correlation and other voxel-to-voxel measures, independent component analyses (ICA), and dynamic component analyses (dyn-ICA). CONN is available for resting state data (rsfMRI) as well as task-related designs. It covers the entire pipeline from raw fMRI data to hypothesis testing, including spatial coregistration, ART-based scrubbing, aCompCor strategy for control of physiological and movement confounds, first-level connectivity estimation, and second-level random-effect analyses and hypothesis testing.
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Nieto-Castanon, Alfonso. CONN functional connectivity toolbox (RRID:SCR_009550), Version 20. Hilbert Press, 2020. http://dx.doi.org/10.56441/hilbertpress.2048.3738.
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CONN is a Matlab-based cross-platform software for the computation, display, and analysis of functional connectivity in fMRI (fcMRI). Connectivity measures include seed-to-voxel connectivity maps, ROI-to- ROI connectivity matrices, graph properties of connectivity networks, generalized psychophysiological interaction models (gPPI), intrinsic connectivity, local correlation and other voxel-to-voxel measures, independent component analyses (ICA), and dynamic component analyses (dyn-ICA). CONN is available for resting state data (rsfMRI) as well as task-related designs. It covers the entire pipeline from raw fMRI data to hypothesis testing, including spatial coregistration, ART-based scrubbing, aCompCor strategy for control of physiological and movement confounds, first-level connectivity estimation, and second-level random-effect analyses and hypothesis testing.
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Nieto-Castanon, Alfonso. CONN functional connectivity toolbox (RRID:SCR_009550), Version 19. Hilbert Press, 2019. http://dx.doi.org/10.56441/hilbertpress.1927.9364.
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CONN is a Matlab-based cross-platform software for the computation, display, and analysis of functional connectivity in fMRI (fcMRI). Connectivity measures include seed-to-voxel connectivity maps, ROI-to- ROI connectivity matrices, graph properties of connectivity networks, generalized psychophysiological interaction models (gPPI), intrinsic connectivity, local correlation and other voxel-to-voxel measures, independent component analyses (ICA), and dynamic component analyses (dyn-ICA). CONN is available for resting state data (rsfMRI) as well as task-related designs. It covers the entire pipeline from raw fMRI data to hypothesis testing, including spatial coregistration, ART-based scrubbing, aCompCor strategy for control of physiological and movement confounds, first-level connectivity estimation, and second-level random-effect analyses and hypothesis testing.
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O'Neill, H. B., S. A. Wolfe, and C. Duchesne. Ground ice map of Canada. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/330294.
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This Open File presents national-scale mapping of ground ice conditions in Canada. The mapping depicts a first-order estimate of the combined volumetric percentage of excess ice in the top 5 m of permafrost from segregated, wedge, and relict ice. The estimates for the three ice types are based on modelling by O'Neill et al. (2019) (https://doi.org/10.5194/tc-13-753-2019), and informed by available published values of ground ice content and expert knowledge. The mapping offers an improved depiction of ground ice in Canada at a broad scale, incorporating current knowledge on the associations between geological and environmental conditions and ground ice type and abundance. It provides a foundation for hypothesis testing related to broad-scale controls on ground ice formation, preservation, and melt. Additional compilation of quantitative field data on ground ice and improvements to national-scale surficial geology mapping will allow further assessment and refinement of the representation of ground ice in Canada. Continued research will focus on improving the lateral and vertical representation of ground ice required for incorporation into Earth system models and decision-making. Spatial data files of the mapping are available as downloads with this Open File.