1,720,975 research outputs found
Matrix Spatial Specification models
Full text linkIn this paper we study a family of linear regression models with spatial dependence in the errors and in the dependent variable. The spatial dependence is modeled by arbitrary matrix functions Vn and Mn respectively, indexed by a scalar parameter and, eventually, by two (possibly distinct) weight matrices, D and W.
We define the quasi maximum likelihood estimator and study its asymptotic properties under non-Gaussian errors. We use the results on the general model to define a wide class of spatial models, defined as matrix transformations of a given weight matrix. This family is large enough to encompass some popular models used in the spatial econometric literature, such as SARAR and MESS models. By defining broad families of models, where matrix transformations are associated to distribution functions, we provide some insights into the difference between specifications, with emphasis on advantages and shortcomings as well as on interpretation of the parameters and correspondences between models
Generalized spatial matrix specifications
Full text linkAbstract.: In this article, we propose a model that generalizes some of the most popular choices in spatial linear modeling, such as the SAR and MESS models. Our idea builds on their representation as link functions applied to a spatial weight W, corresponding to the uniform and exponential distributions, respectively. By allowing for more general families of distribution functions, one can encompass both models and capture different spatial patterns. We provide some insights into the difference between specifications, with emphasis on advantages and shortcomings as well as on interpretation of the parameters and correspondences between models. By exploiting the possibility to obtain a formal power series representation of the link family, we define the quasi maximum likelihood estimator and study its asymptotic properties under Gaussian and non Gaussian errors. By applying our approach to data on 2000 US election participation, as in LeSage and Pace (2007), we show that this model is able to capture a finite order neighboring spillover structure, as opposed to the infinite order implied by both the SAR and MESS models
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Voci in Dizionario dell'Economia e della finanza: ARMA/ARIMA; Asintotica, Distribuzione; Autoregressivo, Modello; Aleatoria variabile; Dati; Destagionalizzazione; Distribuzione campionaria; Distribuzione di probabilità; Dummy; variabili Istogramma; Ergodicità; Econometria; EFFICIENZA STATISTICA; Ergodicità; Esperimento; Eteroschedasticità; Filtro; Funzione matematica; Identificabilità; Inferenza Statistica; Istogramma; Limite; Linearità; Matrice; Quantile; Regressione Nonparametrica; Regressione, Modelli e Stimatore di; Robustezza Statistica; Selezione di un Modello; Serie storiche; Stimatore; Test; Test basati sulla funzione di verosimiglianza; Variabile Aleatoria; Variabili Strumentali; Verosimiglianza; Verosimiglianza massima, metodo della.
No full textVariations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Expected shortfall estimators and their use in asset allocation
Full text linkLa perdita attesa (Expected Shortfall - ES) è una misura di rischio che prende in considerazione le perdite maggiori del Valore al Rischio (Value at Risk - VaR). Siccome l’ES ha le proprietà di una misura di rischio coerente, il suo uso nell’allocazione del portafoglio è diventato rilevante. Nella prima sezione, proponiamo dei stimatori per ES, considerando il caso quando abbiamo a disposizione informazioni aggiuntive compresse in un set di variabile esogene. I stimatori sono costruiti partendo dalla rappresentazione equivalente del ES in termini di funzione di distribuzione e funzione quantilica. Nelle sezioni successive, partendo dalla rappresentazione del ES generalizzata tramite una funzione di pesi, il lavoro prosegue con il miglioramento delle proprietà statistiche e di predizione. Nel primo caso, ottimizziamo la funzione di pesi tale da minimizzare la varianza asintotica, mentre, nel secondo caso, la funzione di pesi minimizza l’errore di predizione dello stimatore. Inoltre, pensando al uso dei stimatori nelle applicazioni finanziarie, costruiamo un modello base di allocazione di portafoglio che massimizza il rendimento atteso con un vincolo sul ES.The Expected Shortfall (ES) is a risk measure that averages out all losses more severe than
the Value at Risk (VaR). As the ES shares the properties of coherent risk measures, its use
as risk constraint in asset allocation has became relevant. First of all, we propose estimators
for ES, considering the important case when additional information as some set of regressors
is available. The estimators are based on the equivalent representation of ES in terms of the
conditional distribution function and the conditional quantile function. Within the estimation
framework, departing from a generalized weighted representation of ES, we work on improving
the statistical and forecasting properties of the weighted estimators. In the first case, we
derive the weighting that minimizes the asymptotic variance of the estimators, while, in the
second case, the weighting minimizes some suitably defined forecast error. Nevertheless we
are concerned with the use of these estimators in financial applications and construct a simple
asset allocation model that maximizes expected return with a loss constraint on ES
- …
