Estimating the Critical Parameter in Almost Stochastic Dominance from Insurance Deductibles

2020 ◽  
Author(s):  
Yi-Chieh Huang ◽  
Kamhon Kan ◽  
Larry Y. Tzeng ◽  
Kili C. Wang
Keyword(s):  
Real World ◽  
Upper Bound ◽  
Stochastic Dominance ◽  
Critical Parameter ◽  
Experimental Studies ◽  
Decision Makers ◽  
The Other ◽  
Real World Data ◽  
Upper Bound Estimate ◽  
Almost Stochastic Dominance

Knowing how small a violation of stochastic dominance rules would be accepted by most individuals is a prerequisite to applying almost stochastic dominance criteria. Unlike previous laboratory-experimental studies, this paper estimates an acceptable violation of stochastic dominance rules with 939,690 real world data observations on a choice of deductibles in automobile theft insurance. We find that, for all policyholders in the sample who optimally chose a low deductible, the upper bound estimate of the acceptable violation ratio is 0.0014, which is close to zero. On the other hand, considering that most decision makers, such as 99% (95%) of the policyholders in the sample, optimally chose the low deductible, the upper bound estimate of the acceptable violation ratio is 0.0405 (0.0732). Our results provide reference values for the acceptable violation ratio for applying almost stochastic dominance rules. This paper was accepted by Manel Baucells, decision analysis.

scholarly journals An upper-bound estimate for the accuracy of glacier volume–area scaling

2013 ◽  
Vol 7 (6) ◽  
pp. 1707-1720 ◽  
Author(s):  
D. Farinotti ◽  
M. Huss
Keyword(s):  
Volume Change ◽  
Real World ◽  
Upper Bound ◽  
Systematic Bias ◽  
Volume Changes ◽  
Real World Data ◽  
Ice Volume ◽  
Lower Accuracy ◽  
Upper Bound Estimate ◽  
The Impact

Abstract. Volume–area scaling is the most popular method for estimating the ice volume of large glacier samples. Here, a series of resampling experiments based on different sets of synthetic data is presented in order to derive an upper-bound estimate (i.e. a level achieved only within ideal conditions) for its accuracy. For real-world applications, a lower accuracy has to be expected. We also quantify the maximum accuracy expected when scaling is used for determining the glacier volume change, and area change of a given glacier population. A comprehensive set of measured glacier areas, volumes, area and volume changes is evaluated to investigate the impact of real-world data quality on the so-assessed accuracies. For populations larger than a few thousand glaciers, the total ice volume can be recovered within 30% if all data currently available worldwide are used for estimating the scaling parameters. Assuming no systematic bias in ice volume measurements, their uncertainty is of secondary importance. Knowing the individual areas of a glacier sample for two points in time allows recovering the corresponding ice volume change within 40% for populations larger than a few hundred glaciers, both for steady-state and transient geometries. If ice volume changes can be estimated without bias, glacier area changes derived from volume–area scaling show similar uncertainties to those of the volume changes. This paper does not aim at making a final judgement on the suitability of volume–area scaling as such, but provides the means for assessing the accuracy expected from its application.

scholarly journals An upper-bound estimate for the accuracy of volume-area scaling

2013 ◽  
Vol 7 (3) ◽  
pp. 2293-2331 ◽  
Author(s):  
D. Farinotti ◽  
M. Huss
Keyword(s):  
Volume Change ◽  
Upper Bound ◽  
Synthetic Data ◽  
Volume Changes ◽  
Real World Data ◽  
Secondary Importance ◽  
Ice Volume ◽  
Volume Measurements ◽  
Upper Bound Estimate ◽  
The Impact

Abstract. Volume-area scaling is the most popular method for estimating the ice volume of large glacier samples. Here, a series of resampling experiments based on different sets of synthetic data are presented in order to derive an upper-bound estimate (i.e. a level achieved only with ideal conditions) for the accuracy of its application. We also quantify the maximum accuracy expected when scaling is used for determining the glacier volume change, and area change of a given glacier population. A comprehensive set of measured glacier areas, volumes, area and volume changes is evaluated to investigate the impact of real-world data quality on the so assessed accuracies. For populations larger than a few thousand glaciers, the total ice volume can be recovered within 30% if all measurements available worldwide are used for estimating the scaling coefficients. Assuming no systematic biases in ice volume measurements, their uncertainty is of secondary importance. Knowing the individual areas of a glacier sample for two points in time allows recovering the corresponding ice volume change within 40% for populations larger than a few hundred glaciers, both for steady-state and transient geometries. If ice volume changes can be estimated without bias, glacier area changes derived from volume-area scaling show similar uncertainties as for the volume changes. This paper does not aim at making a final judgement about the suitability of volume-area scaling, but provides the means for assessing the accuracy expected from its application.

Probabilistic Models for Social Media Mining

2014 ◽  
pp. 95-105
Author(s):  
Flora S. Tsai
Keyword(s):  
Social Media ◽  
Real World ◽  
Probabilistic Models ◽  
The Other ◽  
Media Content ◽  
Real World Data ◽  
Social Media Mining ◽  
Additional Information ◽  
Classification Framework ◽  
Media Mining

This paper proposes probabilistic models for social media mining based on the multiple attributes of social media content, bloggers, and links. The authors present a unique social media classification framework that computes the normalized document-topic matrix. After comparing the results for social media classification on real-world data, the authors find that the model outperforms the other techniques in terms of overall precision and recall. The results demonstrate that additional information contained in social media attributes can improve classification and retrieval results.

scholarly journals What type of clinical evidence is needed to assess medical devices?

2016 ◽  
Vol 25 (141) ◽  
pp. 259-265 ◽  
Author(s):  
Rosanna Tarricone ◽  
Paola Roberta Boscolo ◽  
Patrizio Armeni
Keyword(s):  
Medical Therapy ◽  
Real World ◽  
Clinical Evidence ◽  
Experimental Studies ◽  
Bias Reduction ◽  
Economic Evaluations ◽  
Real World Data ◽  
Relevant Evidence ◽  
Randomised Controlled ◽  
Matching Techniques

The objective of this mini-review is to discuss the role of real-world studies as a source of clinical evidence when experimental studies, such as randomised controlled trials (RCTs), are not available. Waiting for RCT evidence when the technology is diffusing could be anti-economical, inefficient from the policy perspective and methodologically questionable.We explain how real-world studies could provide relevant evidence to decision makers. Matching techniques are discussed as a viable solution for bias reduction.We describe a case study concerning a cost-effectiveness analysis based on real-world data of a technology already in use: Mitraclip combined with medical therapy versus medical therapy alone in patients with moderate-to-severe mitral regurgitation. The CEA has encountered the scepticism of most reviewers, due not to the statistical methodology but to the fact that the study was observational and not experimental. Editors and reviewers converged in considering real-world economic evaluations premature in the absence of a RCT, even if in the meantime the technology had been implanted >30 000 times. We believe there is a need to acknowledge the importance of real-world studies, and engage the scientific community in the promotion and use of clinical evidence produced through observational studies.

scholarly journals Parliamentary Voting Procedures: Agenda Control, Manipulation, and Uncertainty

2017 ◽  
Vol 59 ◽  
pp. 133-173 ◽  
Author(s):  
Robert Bredereck ◽  
Jiehua Chen ◽  
Rolf Niedermeier ◽  
Toby Walsh
Keyword(s):  
Polynomial Time ◽  
Experimental Studies ◽  
The Other ◽  
Real World Data ◽  
Agenda Control ◽  
Voting Procedures ◽  
Specific Alternative ◽  
The One ◽  
Amendment Procedure ◽  
Multiple Stages

We study computational problems for two popular parliamentary voting procedures: the amendment procedure and the successive procedure. They work in multiple stages where the result of each stage may influence the result of the next stage. Both procedures proceed according to a given linear order of the alternatives, an agenda. We obtain the following results for both voting procedures: On the one hand, deciding whether one can make a specific alternative win by reporting insincere preferences by the fewest number of voters, the Manipulation problem, or whether there is a suitable ordering of the agenda, the Agenda Control problem, takes polynomial time. On the other hand, our experimental studies with real-world data indicate that most preference profiles cannot be manipulated by only few voters and a successful agenda control is typically impossible. If the voters' preferences are incomplete, then deciding whether an alternative can possibly win is NP-hard for both procedures. Whilst deciding whether an alternative necessarily wins is coNP-hard for the amendment procedure, it is polynomial-time solvable for the successive procedure.

scholarly journals Sampling for Approximate Maximum Search in Factorized Tensor

2017 ◽  
Author(s):  
Zhi Lu ◽  
Yang Hu ◽  
Bing Zeng
Keyword(s):  
Theoretical Analysis ◽  
Collaborative Filtering ◽  
Real World ◽  
State Of The Art ◽  
The Other ◽  
Data Sets ◽  
Real World Data ◽  
Parafac Model ◽  
The Matrix ◽  
Special Case

Factorization models have been extensively used for recovering the missing entries of a matrix or tensor. However, directly computing all of the entries using the learned factorization models is prohibitive when the size of the matrix/tensor is large. On the other hand, in many applications, such as collaborative filtering, we are only interested in a few entries that are the largest among them. In this work, we propose a sampling-based approach for finding the top entries of a tensor which is decomposed by the CANDECOMP/PARAFAC model. We develop an algorithm to sample the entries with probabilities proportional to their values. We further extend it to make the sampling proportional to the $k$-th power of the values, amplifying the focus on the top ones. We provide theoretical analysis of the sampling algorithm and evaluate its performance on several real-world data sets. Experimental results indicate that the proposed approach is orders of magnitude faster than exhaustive computing. When applied to the special case of searching in a matrix, it also requires fewer samples than the other state-of-the-art method.

Probabilistic Models for Social Media Mining

2011 ◽  
Vol 6 (1) ◽  
pp. 13-24 ◽  
Author(s):  
Flora S. Tsai
Keyword(s):  
Social Media ◽  
Real World ◽  
Probabilistic Models ◽  
The Other ◽  
Media Content ◽  
Real World Data ◽  
Social Media Mining ◽  
Additional Information ◽  
Classification Framework ◽  
Media Mining

This paper proposes probabilistic models for social media mining based on the multiple attributes of social media content, bloggers, and links. The authors present a unique social media classification framework that computes the normalized document-topic matrix. After comparing the results for social media classification on real-world data, the authors find that the model outperforms the other techniques in terms of overall precision and recall. The results demonstrate that additional information contained in social media attributes can improve classification and retrieval results.

An Evaluation of Turkey's NUTS Level 1 Regions According to Banking Sector With MULTIMOORA Method

2017 ◽  
pp. 13-33
Author(s):  
Onur Önay
Keyword(s):  
Decision Making ◽  
Real World ◽  
Banking Sector ◽  
Decision Makers ◽  
Multi Criteria Decision Making ◽  
Real World Data ◽  
Hypothetical Data ◽  
Level 1 ◽  
Spreadsheet Software ◽  
Multimoora Method

In the study, The Nomenclature of Territorial Units for Statistics (NUTS) Level 1 regions of Turkey are evaluated with MULTIMOORA Method according to banking sector using hypothetical data which are adapted from real world data. There are 12 regions as alternatives which are assessed with 6 objectives. Calculations are made by using MS Excel which is powerful spreadsheet software. This application is an example how multi criteria decision making methods can use when a manager making decision. Results are given as lists of regions ranking and commented. By this way, it is shown that how the multi criteria decision making methods can help to decision makers.

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