1,720,958 research outputs found
Estimating Distortion Risk Measures Under Truncated and Censored Data Scenarios
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ABSTRACT\\
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ESTIMATING DISTORTION RISK MEASURES UNDER TRUNCATED AND CENSORED DATA SCENARIOS
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~In insurance data analytics and actuarial practice, a broad class of
risk measures -- {\em distortion risk measures\/} -- are used to capture
the riskiness of the distribution tail. Point and interval estimates of
the risk measures are then employed to price extreme events, to develop
reserves, to design risk transfer strategies, and to allocate capital.
When solving such problems, the main statistical challenge is to choose
an appropriate estimate of a risk measure and to assess its variability.
In this context, the empirical nonparametric approach is the simplest
one to use, but it lacks efficiency due to the scarcity of data in
the tails. On the other hand, parametric estimators, although prone
to model mis-specification, can improve estimators\u27 efficiency
significantly. Moreover, they can easily accommodate data truncation
and censoring that are common features of insurance loss data.
The first objective of this dissertation is to derive the asymptotic
distributions of empirical and parametric estimators of distortion
risk measures under the truncated and censored data scenarios. For
parametric estimation, we use maximum likelihood (ML) and percentile
matching (PM) procedures. The risk measures we consider include:
{\em value-at-risk\/} (VaR), {\em conditional tail expectation\/}
({\sc cte}), {\em proportional hazards transform\/} ({\sc pht}),
{\em Wang transform\/} ({\sc wt}), and {\em Gini shortfall\/}
({\sc gs}). Conditions under which these measures are finite are
studied rigorously. The ML and PM estimators of the risk measures
are derived for three severity models (with identical support):
shifted exponential, Pareto I, and shifted lognormal. Their
asymptotic properties are established and compared with those of
the empirical estimators. Then, the second objective of the
dissertation is to cross-validate and augment the theoretical
results using simulations. Finally, the third objective is to
provide a few numerical examples involving applications of the
new estimators to actual reinsurance data
Estimating Distortion Risk Measures Under Truncated and Censored Data Scenarios
No full text\begin{center} ABSTRACT\\ \vspace{0.4in} ESTIMATING DISTORTION RISK MEASURES UNDER TRUNCATED AND CENSORED DATA SCENARIOS \end{center} \doublespacing \noindent ~In insurance data analytics and actuarial practice, a broad class of risk measures -- {\em distortion risk measures\/} -- are used to capture the riskiness of the distribution tail. Point and interval estimates of the risk measures are then employed to price extreme events, to develop reserves, to design risk transfer strategies, and to allocate capital. When solving such problems, the main statistical challenge is to choose an appropriate estimate of a risk measure and to assess its variability. In this context, the empirical nonparametric approach is the simplest one to use, but it lacks efficiency due to the scarcity of data in the tails. On the other hand, parametric estimators, although prone to model mis-specification, can improve estimators' efficiency significantly. Moreover, they can easily accommodate data truncation and censoring that are common features of insurance loss data. The first objective of this dissertation is to derive the asymptotic distributions of empirical and parametric estimators of distortion risk measures under the truncated and censored data scenarios. For parametric estimation, we use maximum likelihood (ML) and percentile matching (PM) procedures. The risk measures we consider include: {\em value-at-risk\/} (VaR), {\em conditional tail expectation\/} ({\sc cte}), {\em proportional hazards transform\/} ({\sc pht}), {\em Wang transform\/} ({\sc wt}), and {\em Gini shortfall\/} ({\sc gs}). Conditions under which these measures are finite are studied rigorously. The ML and PM estimators of the risk measures are derived for three severity models (with identical support): shifted exponential, Pareto I, and shifted lognormal. Their asymptotic properties are established and compared with those of the empirical estimators. Then, the second objective of the dissertation is to cross-validate and augment the theoretical results using simulations. Finally, the third objective is to provide a few numerical examples involving applications of the new estimators to actual reinsurance data.2021-02-2
Computing and Estimating Distortion Risk Measures: How to Handle Analytically Intractable Cases?
No full textIn insurance data analytics and actuarial practice, distortion risk measures are used to capture the riskiness of the distribution tail. Point and interval estimates of the risk measures are then employed to price extreme events, to develop reserves, to design risk transfer strategies, and to allocate capital. Often the computation of those estimates relies on Monte Carlo simulations, which, depending upon the complexity of the problem, can be very costly in terms of required expertise and computational time. In this article, we study analytic and numerical evaluation of distortion risk measures, with the expectation that the proposed formulas or inequalities will reduce the computational burden. Specifically, we consider several distortion risk measures––value-at-risk (VaR), conditional tail expectation (cte), proportional hazards transform (pht), Wang transform (wt), and Gini shortfall (gs)––and evaluate them when the loss severity variable follows shifted exponential, Pareto I, and shifted lognormal distributions (all chosen to have the same support), which exhibit common distributional shapes of insurance losses. For these choices of risk measures and loss models, only the VaR and cte measures always possess explicit formulas. For pht, wt, and gs, there are cases when the analytic treatment of the measure is not feasible. In the latter situations, conditions under which the measure is finite are studied rigorously. In particular, we prove several theorems that specify two-sided bounds for the analytically intractable cases. The quality of the bounds is further investigated by comparing them with numerically evaluated risk measures. Finally, a simulation study involving application of those bounds in statistical estimation of the risk measures is also provided
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
Variations 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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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