Results 1  10
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20
Assessment and Propagation of Model Uncertainty
, 1995
"... this paper I discuss a Bayesian approach to solving this problem that has long been available in principle but is only now becoming routinely feasible, by virtue of recent computational advances, and examine its implementation in examples that involve forecasting the price of oil and estimating the ..."
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Cited by 108 (0 self)
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this paper I discuss a Bayesian approach to solving this problem that has long been available in principle but is only now becoming routinely feasible, by virtue of recent computational advances, and examine its implementation in examples that involve forecasting the price of oil and estimating the chance of catastrophic failure of the U.S. Space Shuttle.
Intelligent Support for Exploratory Data Analysis
 Journal of Computational and Graphical Statistics
, 1998
"... Exploratory data analysis (EDA) is as much a matter of strategy as of selecting specific statistical operations. We have developed a knowledgebased planning system, called Aide, to help users with EDA. Aide strikes a balance between conventional statistical packages, which need guidance for ever ..."
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Cited by 21 (3 self)
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Exploratory data analysis (EDA) is as much a matter of strategy as of selecting specific statistical operations. We have developed a knowledgebased planning system, called Aide, to help users with EDA. Aide strikes a balance between conventional statistical packages, which need guidance for every step in the exploration, and autonomous systems, which leave the user entirely out of the decisionmaking process. Aide's processing is based on artificial intelligence planning techniques, which give us a useful means of representing some types of statistical strategy. In this article we describe the design of Aide and its behavior in exploring a small, complex dataset. Keywords: exploratory data analysis, artificial intelligence 1 1 Strategic aspects of exploration Exploring data is as much a matter of strategy as of selecting specific statistical operations. In his introduction to exploratory data analysis, for example, Tukey begins by laying out some general guidelines for desc...
The quantitative modeling of operational risk: between gandh and EVT
 ASTIN Bulletin
, 2007
"... Operational risk has become an important risk component in the banking and insurance world. The availability of (few) reasonable data sets has given some authors the opportunity to analyze operational risk data and to propose different models for quantification. As proposed in Dutta and Perry [10], ..."
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Cited by 15 (8 self)
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Operational risk has become an important risk component in the banking and insurance world. The availability of (few) reasonable data sets has given some authors the opportunity to analyze operational risk data and to propose different models for quantification. As proposed in Dutta and Perry [10], the parametric gandh distribution has recently emerged as an interesting candidate. In our paper, we discuss some fundamental properties of the gandh distribution and their link to extreme value theory (EVT). We show that for the gandh distribution, convergence of the excess distribution to the generalized Pareto distribution (GPD) is extremely slow and therefore quantile estimation using EVT may lead to inaccurate results if data are well modeled by a gandh distribution. We further discuss the subadditivity property of ValueatRisk (VaR) for gandh random variables and show that for reasonable g and h parameter values, superadditivity may appear when estimating high quantiles. Finally, we look at the gandh distribution in the oneclaimcausesruin paradigm.
An Adjusted Boxplot for Skewed Distributions
, 2006
"... The boxplot is a very popular graphical tool to visualize the distribution of continuous unimodal data. It shows information about the location, spread, skewness as well as the tails of the data. However, since the fences are derived from the normal distribution, usually too many points are class ..."
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Cited by 8 (2 self)
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The boxplot is a very popular graphical tool to visualize the distribution of continuous unimodal data. It shows information about the location, spread, skewness as well as the tails of the data. However, since the fences are derived from the normal distribution, usually too many points are classified as outliers when the data are skewed. We present an adjustment of the boxplot that includes a robust measure of skewness in the determination of the whiskers. We show with several examples and simulation results that this adjusted boxplot gives a more accurate representation of the data and of possible outliers.
2001a. On quantitative formulation of nationwide human environment index. Final Report. Division of Early Warning and Assessment
, 2001
"... Prepared with partial support from the United Nations Environment Programme (UNEP) Division of Early Warning and Assessment (DEWA), MOU Number FP/102000012218. The contents have not been subjected to Programme review and therefore do not necessarily reflect the views of the Programme ..."
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Cited by 5 (4 self)
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Prepared with partial support from the United Nations Environment Programme (UNEP) Division of Early Warning and Assessment (DEWA), MOU Number FP/102000012218. The contents have not been subjected to Programme review and therefore do not necessarily reflect the views of the Programme
Interactions and Outliers in the TwoWay Analysis of Variance
 Annals of Statistics
, 1998
"... . The twoway analysis of variance with interactions is a well established and integral part of statistics. In spite of its long standing it is hown that the standard definition of interactions is counter intuitive and obfuscates rather than clarifies. A different definition of interaction is given ..."
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Cited by 5 (2 self)
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. The twoway analysis of variance with interactions is a well established and integral part of statistics. In spite of its long standing it is hown that the standard definition of interactions is counter intuitive and obfuscates rather than clarifies. A different definition of interaction is given which amongst other advantages allows the detection of interactions even in the case of one observation per cell. A characterization of unconditionally identifiable interaction patterns is given and it is proved that such patterns can be identified by the L 1 functional. The unconditionally identifiable interaction patterns describe the optimal breakdown behaviour of any equivariant location functional from which it follows that the L 1 functional has optimal breakdown behaviour. Possible lack of uniqueness of the L 1 functional can be overcome using an Mfunctional with an external scale derived independently from the observations. The resulting procedures are applied to some data ...
Toward the Integration of Exploration and Modeling in a Planning Framework
 IN PROCEEDINGS OF THE AAAI94 WORKSHOP IN KNOWLEDGE DISCOVERY IN DATABASES
, 1994
"... Statistical operations are often facilitated by other operations. We can facilitate modeling operations by testing their input for irregularities and removing problems wherever possible. A planning representation is wellsuited to this task. We describe the representation used in Igor, a system f ..."
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Cited by 4 (4 self)
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Statistical operations are often facilitated by other operations. We can facilitate modeling operations by testing their input for irregularities and removing problems wherever possible. A planning representation is wellsuited to this task. We describe the representation used in Igor, a system for exploratory data analysis, and its integration with two modeling systems, Pearl's IC and Cohen's FBD. We show that introducing outliers into the inputs of the algorithms can influence their performance. We demonstrate that a planning representation offers a flexible way of integrating outlier detection and removal into the modeling process, taking account of specific characteristics of the modeling operations involved.
Mining Exceptions And Quantitative Association Rules In Olap Data Cube
, 1999
"... People nowadays are relying more and more on OLAP data to find business solutions. A typical OLAP data cube usually contains four to eight dimensions, with two to six hierarchical levels and tens to hundreds of categories for each dimension. It is often too large and has too many levels for users to ..."
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Cited by 2 (0 self)
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People nowadays are relying more and more on OLAP data to find business solutions. A typical OLAP data cube usually contains four to eight dimensions, with two to six hierarchical levels and tens to hundreds of categories for each dimension. It is often too large and has too many levels for users to browse it effectively. In this thesis we propose a system prototype which will guide users to efficiently explore exceptions in data cubes. It automatically computes the degree of exceptions for cube cells at different aggregation levels. When user browses the cube, exceptional cells as well as interesting drillingdown paths that will lead to lower level exceptions are highlighted according to their interestingness. Different statistical methods such as loglinear model, adapted linear model and Ztests are used to compute the degree of exceptions. We present algorithms and address the issue of improving the performance on large data sets. Our study on exceptions leads to mining quantitati...
Comparing MetaAnalytic Moderator Estimation Techniques Under Realistic Conditions
"... One of the most problematic issues in contemporary metaanalysis is the estimation and interpretation of moderating effects. Monte Carlo analyses are developed in this article that compare bivariate correlations, ordinary least squares and weighted least squares (WLS) multiple regression, and hierar ..."
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Cited by 1 (1 self)
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One of the most problematic issues in contemporary metaanalysis is the estimation and interpretation of moderating effects. Monte Carlo analyses are developed in this article that compare bivariate correlations, ordinary least squares and weighted least squares (WLS) multiple regression, and hierarchical subgroup (HS) analysis for assessing the influence of continuous moderators under conditions of multicollinearity and skewed distribution of study sample sizes (heteroscedasticity). The results show that only WLS is largely unaffected by multicollinearity and heteroscedasticity, whereas the other techniques are substantially weakened. Of note, HS, one of the most popular methods, typically provides the most inaccurate results, whereas WLS, one of the least popular methods, typically provides the most accurate results. The use of metaanalysis as a mode for theory testing has grown considerably in recent years, a growth that is verging on maturation. In the beginning, the great challenge for metaanalysis was mere acceptance. There was substantial doubt that such a technique was statistically sound, and consequently many of the initial publications in this area were focused on education as well as
Bayesian Assessment of GoodnessofFit against Nonparametric Alternatives
, 2000
"... The classical chisquare test of goodnessoffit compares the hypothesis that data arise from some parametric family of distributions, against the nonparametric alternative that they arise from some other distribution. However, the chisquare test requires continuous data to be grouped into arbitrar ..."
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The classical chisquare test of goodnessoffit compares the hypothesis that data arise from some parametric family of distributions, against the nonparametric alternative that they arise from some other distribution. However, the chisquare test requires continuous data to be grouped into arbitrary categories. Furthermore, as the test is based upon an approximation, it can only be used if there is su#cient data. In practice, these requirements are often wasteful of information and overly restrictive. The authors explore the use of the fractional Bayes factor to obtain a Bayesian alternative to the chisquare test when no specific prior information is available. They consider the extent to which their methodology can handle small data sets and continuous data without arbitrary grouping. R ESUM E Le test classique d'ajustement du khideux confronte l'hypothese que les observations proviennent d'une famille parametrique de lois a l'hypothese non parametrique qu'elles sont issues d'un...