Relevant bibliographies by topics / Statistic risk

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Statistic risk'

Author: Grafiati
Published: 4 June 2021
Last updated: 18 February 2022

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Journal articles on the topic "Statistic risk"

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Shen, Xi, Chang-Xing Ma, Kam C. Yuen, and Guo-Liang Tian. "Common risk difference test and interval estimation of risk difference for stratified bilateral correlated data." Statistical Methods in Medical Research 28, no. 8 (June 19, 2018): 2418–38. http://dx.doi.org/10.1177/0962280218781988.

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Bilateral correlated data are often encountered in medical researches such as ophthalmologic (or otolaryngologic) studies, in which each unit contributes information from paired organs to the data analysis, and the measurements from such paired organs are generally highly correlated. Various statistical methods have been developed to tackle intra-class correlation on bilateral correlated data analysis. In practice, it is very important to adjust the effect of confounder on statistical inferences, since either ignoring the intra-class correlation or confounding effect may lead to biased results. In this article, we propose three approaches for testing common risk difference for stratified bilateral correlated data under the assumption of equal correlation. Five confidence intervals of common difference of two proportions are derived. The performance of the proposed test methods and confidence interval estimations is evaluated by Monte Carlo simulations. The simulation results show that the score test statistic outperforms other statistics in the sense that the former has robust type [Formula: see text] error rates with high powers. The score confidence interval induced from the score test statistic performs satisfactorily in terms of coverage probabilities with reasonable interval widths. A real data set from an otolaryngologic study is used to illustrate the proposed methodologies.
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Tian, Dejian, and Xinli Suo. "A note on convex risk statistic." Operations Research Letters 40, no. 6 (November 2012): 551–53. http://dx.doi.org/10.1016/j.orl.2012.09.011.

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Deng, Xiaochuan, and Fei Sun. "Regulator-Based Risk Statistics for Portfolios." Discrete Dynamics in Nature and Society 2020 (July 9, 2020): 1–6. http://dx.doi.org/10.1155/2020/7015267.

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Risk statistic is a critical factor not only for risk analysis but also for financial application. However, the traditional risk statistics may fail to describe the characteristics of regulator-based risk. In this paper, we consider the regulator-based risk statistics for portfolios. By further developing the properties related to regulator-based risk statistics, we are able to derive dual representation for such risk.
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Ocak, Gurbey, Chava Ramspek, Maarten B. Rookmaaker, Peter J. Blankestijn, Marianne C. Verhaar, Willem Jan W. Bos, Friedo W. Dekker, and Merel van Diepen. "Performance of bleeding risk scores in dialysis patients." Nephrology Dialysis Transplantation 34, no. 7 (January 4, 2019): 1223–31. http://dx.doi.org/10.1093/ndt/gfy387.

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Abstract Background Bleeding risk scores have been created to identify patients with an increased bleeding risk, which could also be useful in dialysis patients. However, the predictive performances of these bleeding risk scores in dialysis patients are unknown. Therefore, the aim of this study was to validate existing bleeding risk scores in dialysis patients. Methods A cohort of 1745 incident dialysis patients was prospectively followed for 3 years during which bleeding events were registered. We evaluated the discriminative performance of the Hypertension, Abnormal kidney and liver function, Stroke, Bleeding, Labile INR, Elderly and Drugs or alcohol (HASBLED), the AnTicoagulation and Risk factors In Atrial fibrillation (ATRIA), the Hepatic or kidney disease, Ethanol abuse, Malignancy, Older age, Reduced platelet count or Reduced platelet function, Hypertension, Anaemia, Genetic factors, Excessive fall risk and Stroke (HEMORR2HAGES) and the Outcomes Registry for Better Informed Treatment (ORBIT) bleeding risk scores by calculating C-statistics with 95% confidence intervals (CI). In addition, calibration was evaluated by comparing predicted and observed risks. Results Of the 1745 dialysis patients, 183 patients had a bleeding event, corresponding to an incidence rate of 5.23/100 person-years. The HASBLED [C-statistic of 0.58 (95% CI 0.54–0.62)], ATRIA [C-statistic of 0.55 (95% CI 0.51–0.60)], HEMORR2HAGES [C-statistic of 0.56 (95% CI 0.52–0.61)] and ORBIT [C-statistic of 0.56 (95% CI 0.52–0.61)] risk scores had poor discriminative performances in dialysis patients. Furthermore, the calibration analyses showed that patients with a low risk of bleeding according to the HASBLED, ATRIA, HEMORR2HAGES and ORBIT bleeding risk scores had higher incidence rates for bleeding in our cohort than predicted. Conclusions The HASBLED, ATRIA, HEMORR2HAGES and ORBIT bleeding risk scores had poor predictive abilities in dialysis patients. Therefore, these bleeding risk scores may not be useful in this population.
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Molinari, Nicolas. "A U-statistic test in competing risk models." Comptes Rendus Mathematique 341, no. 5 (September 2005): 317–22. http://dx.doi.org/10.1016/j.crma.2005.07.016.

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Zhu, Hong Han. "Financial Market Risk Overflow Modeling and Inspection Based on Support Vector Machine." Applied Mechanics and Materials 571-572 (June 2014): 1189–94. http://dx.doi.org/10.4028/www.scientific.net/amm.571-572.1189.

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Combined granger test statistics based on VaR and CCF and machine learning theory to establish financial market risk overflow model of support vector machine. To analyze risk information overflow by the statistic characteristics of risk information overflow structure. The model can more effective to test variety forms of risk overflow, Main performance is the extreme risk for information received peripheral selectivity and market volatility non-stability. Emerging markets characteristics in A Shares is evident, the performance are the selective reception of outside extreme risk information. Empirical results demonstrate that models have certain value to the management and control of overflow risks in financial markets.
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Überla, K., W. Ahlborn, and H. J. Tuz. "Risk Analysis in Cohort Studies with Heterogeneous Strata. A Global χ2-Test for Dose-Response Relationship, Generalizing the Mantel-Haenszel Procedure." Methods of Information in Medicine 29, no. 02 (1990): 113–21. http://dx.doi.org/10.1055/s-0038-1636366.

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AbstractIn cohort studies the Mantel-Haenszel estimator OR̂ MH is computed from sample data and is used as a point estimator of relative risk. Test-based confidence intervals are estimated with the help of the asymptotic chi-squared distributed MH-statistic χ2 MHS . The Mantel-exten-sion-chi-squared is used as a test statistic for a dose-response relationship. Both test statistics – the Mantel-Haenszel-chi as well as the Mantel-extension-chi – assume homogeneity of risk across strata, which is rarely present. Also an extended nonparametric statistic, proposed by Terpstra, which is based on the Mann-Whitney-statistics assumes homogeneity of risk across strata.We have earlier defined four risk measures RR k j (k = 1,2,...,4) in the population and considered their estimates and the corresponding asymptotic distributions. In order to overcome the homogeneity assumption we use the δ-method to get “test-based” confidence intervals. Because the four risk measures RR k j are presented as functions of four weights gik we give, consequently, the asymptotic variances of these risk estimators also as functions of the weights g ik in a closed form. Approximations to these variances are given.For testing a dose-response relationship we propose a new class of χ2(1)-distributed global measures Ĝk and the corresponding global χ2-test. In contrast to the Mantel-extension-chi homogeneity of risk across strata must not be assumed. These global test statistics are of the Wald type for composite hypotheses. The Mantel-extension-chi is a special case of the global-chi statistic and it is further shown that the Mantel-extension-chi can be expressed as a special weighted Terpstra statistic. Formulas for computing estimators of the global measures are provided. Three elaborated examples with hypothetical data of varying structure show, that the Mantel-extension-chi is systematically biased, generally overestimates the dose-response relation and leads to wrong conclusions, when heterogeneity is present. This is consistent with our theoretical considerations. In case of heterogeneity, when one wants to test an association between exposure and effect, or a dose-response relationship, the new global-χ2-test should be used in cohort studies.
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McKian, Kevin P., Carol A. Reynolds, Daniel W. Visscher, Aziza Nassar, Derek C. Radisky, Robert A. Vierkant, Amy C. Degnim, et al. "Novel Breast Tissue Feature Strongly Associated With Risk of Breast Cancer." Journal of Clinical Oncology 27, no. 35 (December 10, 2009): 5893–98. http://dx.doi.org/10.1200/jco.2008.21.5079.

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Purpose Accurate, individualized risk prediction for breast cancer is lacking. Tissue-based features may help to stratify women into different risk levels. Breast lobules are the anatomic sites of origin of breast cancer. As women age, these lobular structures should regress, which results in reduced breast cancer risk. However, this does not occur in all women. Methods We have quantified the extent of lobule regression on a benign breast biopsy in 85 patients who developed breast cancer and 142 age-matched controls from the Mayo Benign Breast Disease Cohort, by determining number of acini per lobule and lobular area. We also calculated Gail model 5-year predicted risks for these women. Results There is a step-wise increase in breast cancer risk with increasing numbers of acini per lobule (P = .0004). Adjusting for Gail model score, parity, histology, and family history did not attenuate this association. Lobular area was similarly associated with risk. The Gail model estimates were associated with risk of breast cancer (P = .03). We examined the individual accuracy of these measures using the concordance (c) statistic. The Gail model c statistic was 0.60 (95% CI, 0.50 to 0.70); the acinar count c statistic was 0.65 (95% CI, 0.54 to 0.75). Combining acinar count and lobular area, the c statistic was 0.68 (95% CI, 0.58 to 0.78). Adding the Gail model to these measures did not improve the c statistic. Conclusion Novel, tissue-based features that reflect the status of a woman's normal breast lobules are associated with breast cancer risk. These features may offer a novel strategy for risk prediction.
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Gaprindashvili, George, Jianping Guo, Panisara Daorueang, Tian Xin, and Pooyan Rahimy. "A New Statistic Approach towards Landslide Hazard Risk Assessment." International Journal of Geosciences 05, no. 01 (2014): 38–49. http://dx.doi.org/10.4236/ijg.2014.51006.

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Vaziri, Sasha, Jacob Wilson, Joseph Abbatematteo, Paul Kubilis, Saptarshi Chakraborty, Khare Kshitij, and Daniel J. Hoh. "Predictive performance of the American College of Surgeons universal risk calculator in neurosurgical patients." Journal of Neurosurgery 128, no. 3 (March 2018): 942–47. http://dx.doi.org/10.3171/2016.11.jns161377.

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OBJECTIVEThe American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) universal Surgical Risk Calculator is an online decision-support tool that uses patient characteristics to estimate the risk of adverse postoperative events. Further validation of this risk calculator in the neurosurgical population is needed; therefore, the object of this study was to assess the predictive performance of the ACS NSQIP Surgical Risk Calculator in neurosurgical patients treated at a tertiary care center.METHODSA single-center retrospective review of 1006 neurosurgical patients treated in the period from September 2011 through December 2014 was performed. Individual patient characteristics were entered into the NSQIP calculator. Predicted complications were compared with actual occurrences identified through chart review and administrative quality coding data. Statistical models were used to assess the predictive performance of risk scores. Traditionally, an ideal risk prediction model demonstrates good calibration and strong discrimination when comparing predicted and observed events.RESULTSThe ACS NSQIP risk calculator demonstrated good calibration between predicted and observed risks of death (p = 0.102), surgical site infection (SSI; p = 0.099), and venous thromboembolism (VTE; p = 0.164) Alternatively, the risk calculator demonstrated a statistically significant lack of calibration between predicted and observed risk of pneumonia (p = 0.044), urinary tract infection (UTI; p < 0.001), return to the operating room (p < 0.001), and discharge to a rehabilitation or nursing facility (p < 0.001). The discriminative performance of the risk calculator was assessed using the c-statistic. Death (c-statistic 0.93), UTI (0.846), and pneumonia (0.862) demonstrated strong discriminative performance. Discharge to a rehabilitation facility or nursing home (c-statistic 0.794) and VTE (0.767) showed adequate discrimination. Return to the operating room (c-statistic 0.452) and SSI (0.556) demonstrated poor discriminative performance. The risk prediction model was both well calibrated and discriminative only for 30-day mortality.CONCLUSIONSThis study illustrates the importance of validating universal risk calculators in specialty-specific surgical populations. The ACS NSQIP Surgical Risk Calculator could be used as a decision-support tool for neurosurgical informed consent with respect to predicted mortality but was poorly predictive of other potential adverse events and clinical outcomes.
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Dissertations / Theses on the topic "Statistic risk"

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Pouliot, William. "Two applications of U-Statistic type processes to detecting failures in risk models and structural breaks in linear regression models." Thesis, City University London, 2010. http://openaccess.city.ac.uk/1166/.

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This dissertation is concerned with detecting failures in Risk Models and in detecting structural breaks in linear regression models. By applying Theorem 2.1 of Szyszkowicz on U-statistic type process, a number of weak convergence results regarding three weighted partial sum processes are established. It is shown that these partial sum processes share certain invariance properties; estimation risk does not affect their weak convergence results and they are also robust to asymmetries in the error process in linear regression models. There is also an application of the methods developed here to a four factor Capital Asset Pricing model where it is shown via the methods developed in Chapter 3 that manager stock selection abilities vary over time.
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Misák, Petr. "Možnosti řízení a minimalizace rizik technologie výroby stavebních materiálů a výrobků pomocí fuzzy logiky a dalších nástrojů risk managementu." Doctoral thesis, Vysoké učení technické v Brně. Fakulta stavební, 2014. http://www.nusl.cz/ntk/nusl-233814.

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The thesis proposes management options and risk minimizing in the field of building materials production technologies and related products using fuzzy logic and other risk management tools. The thesis indicates why some methodologies are not commonly used. The main purpose of this work (thesis) is to propose possible upgrades of standard methods in process capability and risk minimizing related to building materials and products. Markov analysis and fuzzy Markov chains are applied.
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Follestad, Turid. "Stochastic Modelling and Simulation Based Inference of Fish Population Dynamics and Spatial Variation in Disease Risk." Doctoral thesis, Norwegian University of Science and Technology, Faculty of Information Technology, Mathematics and Electrical Engineering, 2003. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-41.

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We present a non-Gaussian and non-linear state-space model for the population dynamics of cod along the Norwegian Skagerak coast, embedded in the framework of a Bayesian hierarchical model. The model takes into account both process error, representing natural variability in the dynamics of a population, and observational error, reflecting the sampling process relating the observed data to true abundances. The data set on which our study is based, consists of samples of two juvenile age-groups of cod taken by beach seine hauls at a set of sample stations within several fjords along the coast. The age-structure population dynamics model, constituting the prior of the Bayesian model, is specified in terms of the recruitment process and the processes of survival for these two juvenile age-groups and the mature population, for which we have no data. The population dynamics is specified on abundances at the fjord level, and an explicit down-scaling from the fjord level to the level of the monitored stations is included in the likelihood, modelling the sampling process relating the observed counts to the underlying fjord abundances.

We take a sampling based approach to parameter estimation using Markov chain Monte Carlo methods. The properties of the model in terms of mixing and convergence of the MCMC algorithm and explored empirically on the basis of a simulated data set, and we show how the mixing properties can be improved by re-parameterisation. Estimation of the model parameters, and not the abundances, is the primary aim of the study, and we also propose an alternative approach to the estimation of the model parameters based on the marginal posterior distribution integrating over the abundances.

Based on the estimated model we illustrate how we can simulate the release of juvenile cod, imitating an experiment conducted in the early 20th century to resolve a controversy between a fisherman and a scientist who could not agree on the effect of releasing cod larvae on the mature abundance of cod. This controversy initiated the monitoring programme generating the data used in our study.

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Eliasson, Hampus. "Values at Risk." Thesis, Uppsala universitet, Statistiska institutionen, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-347408.

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Shen, Hanyang, Bizu Gelaye, Hailiang Huang, Marta B. Rondon, Sixto Sanchez, and Laramie E. Duncan. "Polygenic prediction and GWAS of depression, PTSD, and suicidal ideation/self-harm in a Peruvian cohort." Springer Nature, 2020. http://hdl.handle.net/10757/652459.

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Genome-wide approaches including polygenic risk scores (PRSs) are now widely used in medical research; however, few studies have been conducted in low- and middle-income countries (LMICs), especially in South America. This study was designed to test the transferability of psychiatric PRSs to individuals with different ancestral and cultural backgrounds and to provide genome-wide association study (GWAS) results for psychiatric outcomes in this sample. The PrOMIS cohort (N = 3308) was recruited from prenatal care clinics at the Instituto Nacional Materno Perinatal (INMP) in Lima, Peru. Three major psychiatric outcomes (depression, PTSD, and suicidal ideation and/or self-harm) were scored by interviewers using valid Spanish questionnaires. Illumina Multi-Ethnic Global chip was used for genotyping. Standard procedures for PRSs and GWAS were used along with extra steps to rule out confounding due to ancestry. Depression PRSs significantly predicted depression, PTSD, and suicidal ideation/self-harm and explained up to 0.6% of phenotypic variation (minimum p = 3.9 × 10−6). The associations were robust to sensitivity analyses using more homogeneous subgroups of participants and alternative choices of principal components. Successful polygenic prediction of three psychiatric phenotypes in this Peruvian cohort suggests that genetic influences on depression, PTSD, and suicidal ideation/self-harm are at least partially shared across global populations. These PRS and GWAS results from this large Peruvian cohort advance genetic research (and the potential for improved treatments) for diverse global populations.
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Agering, Harald. "True risk of illiquid investments." Thesis, KTH, Matematik (Inst.), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-233577.

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Alternative assets are becoming a considerable portion of global financial markets. Some of these alternative assets are highly illiquid, and as such they may require more intricate methods for calculating risk and performance statistics accurately. Research on hedge funds has established a pattern of risk being understated and various measures of performance being overstated due to illiquidity of the assets. This paper sets out to prove the existence of such bias and presents methods for removing it. Four mathematical methods aiming to adjust statistics for sparse return series were considered, and an implementation was carried out for data on private equity, real estate and infrastructure assets. The results indicate that there are in general substantial adjustments made to the risk and performance statistics of the illiquid assets when using these methods. In particular, the volatility and market exposure were adjusted upwards while manager skill and risk-adjusted performance were adjusted downwards.
Alternativa tillgångsslag börjar utgöra en avsevärd del av globala finansiella marknader. Vissa av dessa alternativa tillgångsslag är mycket illikvida och kan som sådana kräva mer avancerade metoder för att beräkna nyckeltal för risk och utveckling mer korrekt. Forskning på hedgefonder har kunnat påvisa ett mönster där risk underskattas medan olika nyckeltal för utveckling överskattas till följd av tillgångarnas illikviditet. Målet med denna artikel är att påvisa förekomsten av sådan systematisk avvikelse samt att presentera metoder för att avlägsna densamma. Fyra matematiska metoder framtagna för att justera nyckeltal för glesa dataserier användes, och metoderna implementerades på data för tillgångar i private equity, fastigheter samt infrastruktur. Resultaten antyder att det generellt sett sker betydande justeringar av nyckeltalen för risk och utveckling för de illikvida tillgångsslagen när man tillämpar dessa metoder. Mer specifikt justerades volatiliteten och marknadsexponeringen uppåt medan förvaltarens förmåga och den riskjusterade avkastningen justerades nedåt.
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Svindland, Gregor. "Convex Risk Measures Beyond Bounded Risks." Diss., lmu, 2009. http://nbn-resolving.de/urn:nbn:de:bvb:19-97156.

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Tang, Zhaofeng. "Quantitative risk management under systematic and systemic risks." Diss., University of Iowa, 2019. https://ir.uiowa.edu/etd/7035.

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The contemporary risk management practice emphasizes the interplay of multilevel risks, of which the systematic and systemic risks are considered the main culprits of catastrophic losses. With this in mind, this thesis investigates three important topics in quantitative risk management, in which the systematic and systemic risks play a devastating role. First of all, we center on the design of reinsurance policies that accommodate the joint interests of the insurer and reinsurer by drawing upon the celebrated notion of Pareto optimality in the context of a distortion-risk-measure-based model. Such a topic is of considerable practical interest in the current post financial crisis era when people have witnessed the significant systemic risk posed by the insurance industry and the vulnerability of insurance companies to systemic events. Specifically, we characterize the set of Pareto-optimal reinsurance policies analytically and introduce the Pareto frontier to visualize the insurer-reinsurer trade-off structure geometrically. Another enormous merit of developing the Pareto frontier is the considerable ease with which Pareto-optimal reinsurance policies can be constructed even in the presence of the insurer's and reinsurer's individual risk constraints. A strikingly simple graphical search of these constrained policies is performed in the special cases of value-at-risk and tail value-at-risk. Secondly, we propose probabilistic and structural characterizations for insurance indemnities that are universally marketable in the sense that they appeal to both policyholders and insurers irrespective of their risk preferences and risk profiles. We begin with the univariate case where there is a single risk facing the policyholder, then extend our results to the case where multiple possibly dependent risks co-exist according to a mixture structure capturing policyholder's exposure to systematic and systemic risks. Next, we study the asymptotic behavior of the loss from defaults of a large credit portfolio. We consider a static structural model in which latent variables governing individual defaults follow a mixture structure incorporating idiosyncratic, systematic, and systemic risks. The portfolio effect, namely the decrease in overall risk due to the portfolio size increase, is taken into account. We derive sharp asymptotics for the tail probability of the portfolio loss as the portfolio size becomes large and our main finding is that the occurrence of large losses can be attributed to either the common shock variable or systematic risk factor, whichever has a heavier tail. Finally, we extend the asymptotic study of loss from defaults of a large credit portfolio under an amalgamated model. Aiming at investigating the dependence among the risk components of each obligor, we propose a static structural model in which each obligor's default indicator, loss given default, and exposure at default are respectively governed by three dependent latent variables with exposure to idiosyncratic, systematic, and systemic risks. The asymptotic distribution as well as the asymptotic value-at-risk and expected shortfall of the portfolio loss are obtained. The results are further refined when a specific mixture structure is employed for latent variables.
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Sandberg, Martina. "Credit Risk Evaluation using Machine Learning." Thesis, Linköpings universitet, Statistik och maskininlärning, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-138968.

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In this thesis, we examine the machine learning models logistic regression, multilayer perceptron and random forests in the purpose of discriminate between good and bad credit applicants. In addition to these models we address the problem of imbalanced data with the Synthetic Minority Over-Sampling Technique (SMOTE). The data available have 273 286 entries and contains information about the invoice of the applicant and the credit decision process as well as information about the applicant. The data was collected during the period 2015-2017. With AUC-values at about 73%some patterns are found that can discriminate between customers that are likely to pay their invoice and customers that are not. However, the more advanced models only performed slightly better than the logistic regression.
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Ljung, Carl. "Copula selection and parameter estimation in market risk models." Thesis, KTH, Matematisk statistik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-204420.

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In this thesis, literature is reviewed for theory regarding elliptical copulas (Gaussian, Student’s t, and Grouped t) and methods for calibrating parametric copulas to sets of observations. Theory regarding model diagnostics is also summarized in the thesis. Historical data of equity indices and government bond rates from several geo-graphical regions along with U.S. corporate bond indices are used as proxies of the most significant stochastic variables in the investment portfolio of If P&C. These historical observations are transformed into pseudo-uniform observations, pseudo-observations, using parametric and non-parametric univariate models. The parametric models are fitted using both maximum likelihood and least squares of the quantile function. Ellip-tical copulas are then calibrated to the pseudo-observations using the well known methods Inference Function for Margins (IFM) and Semi-Parametric (SP) as well as compositions of these methods and a non-parametric estimator of Kendall’s tau.The goodness-of-fit of the calibrated multivariate models is assessed in aspect of general dependence, tail dependence, mean squared error as well as by using universal measures such as Akaike and Bayesian Informa-tion Criterion, AIC and BIC. The mean squared error is computed both using the empirical joint distribution and the empirical Kendall distribution function. General dependence is measured using the scale-invariant measures Kendall’s tau, Spearman’s rho, and Blomqvist’s beta, while tail dependence is assessed using Krup-skii’s tail-weighted measures of dependence (see [16]). Monte Carlo simulation is used to estimate these mea-sures for copulas where analytical calculation is not feasible.Gaussian copulas scored lower than Student’s t and Grouped t copulas in every test conducted. However, not all test produced conclusive results. Further, the obtained values of the tail-weighted measures of depen-dence imply a systematically lower tail dependence of Gaussian copulas compared to historical observations.
I den här uppsatsen granskas teori angående elliptiska copulas (Gaussisk, Students t och s.k. Grupperad t) och metoder för att kalibrera parametriska copulas till stickprov av observationer. Uppsatsen summerar även teori kring olika metoder för att analysera och jämföra copula-modeller. Historisk data av aktieindex och stats-obligationer från flera olika geografiska områden samt Amerikanska index för företagsobligationer används för att modellera de huvudsakliga stokastiskt drivande variablerna i investeringsportföljen hos If P&C. Des-sa historiska observationer transformeras med parametriska och icke-parametriska univariata modeller till pseudolikformiga observationer, pseudo-observationer. De parametriska modellerna passas till data med bå-de maximum likelihood och med minsta-kvadratpassning av kvantilfunktionen. Därefter kalibreras elliptiska copulas till pseudo-observationerna med de välkända metoderna Inference Function for Margins (IFM) och Semi-Parametric (SP) samt med blandningar av dessa två metoder och den icke-parametriska estimatorn av Kendalls tau.Hur väl de kalibrerade multivariata modellerna passar de historiska data utvärderas med avseende på ge-nerellt beroende, svansberoende, rotmedelavvikelse samt genom att använda mer allmäna mått som Akaike och Bayesianskt informationskriterium, AIC och BIC. Rotmedelavvikelsen räknas ut både genom att använda den empiriska gemensamma fördelningen och den empiriska Kendall fördelningsfunktionen. Generellt bero-ende mäts med de skalinvarianta måtten Kendalls tau, Spearmans rho och Blomqvists beta, medan svansbe-roende utvärderas med Krupskiis svansviktade beroendemått (se [16]). I de fall där analytiska beräkningsme-toder inte är möjliga för copulas används Monte Carlo-simulering för att skatta dessa mått.De Gaussiska copulas gav sämre resultat än Students t och Grupperad t copulas i varje enskilt test som utfördes. Dock så kan ej alla testresultat anses vara absolut definitiva. Vidare så antyder de erhållna värde-na från de svansviktade beroendemåtten att modellering med Gaussisk copula resulterar i systematiskt lägre svansberoende hos modellen än hos de historiska observationerna.
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Books on the topic "Statistic risk"

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D, Schmidt Klaus. Lectures on risk theory. Stuttgart: Teubner, 1996.

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Statistical sampling and risk analysis in auditing. Hampshire: Gower, 1999.

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Covello, Vincent T. Risk communication, risk statistics, and risk comparisons: A manual for plant managers. Washington, D.C: Chemical Manufacturers Association, 1988.

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Norberg, Ragnar. Risk theory and its statistics environment. Copenhagen: University of Copenhagen, 1988.

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Statistical estimation of epidemiological risk. Chichester: Wiley, 2003.

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Gottfredson, Don M. Statistical approaches to assessing risk. [Washington, DC]: U.S. Dept. of Justice, Office of Justice Programs, Office of Juvenile Justice and Delinquency Prevention, 2002.

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Chance rules: An informal guide to probability, risk and statistics. 2nd ed. New York: Springer, 2008.

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Everitt, Brian. Chance rules: An informal guide to probability, risk, and statistics. New York: Copernicus, 1999.

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Miller, Michael B. Mathematics and Statistics for Financial Risk Management. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118819616.

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De Luca, Giovanni, Danilo Carità, and Francesco Martinelli. Statistical Analysis of Operational Risk Data. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42580-7.

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Book chapters on the topic "Statistic risk"

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Tian, Ze, and Jianjun Han. "Developmental Tendency and Empirical Analysis of Staff’s Boundaryless Career: Statistic Analysis Based on the Experience in China." In Computational Risk Management, 413–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-18387-4_46.

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Mazankova, Martina J. "Statistic of Police of Czech Republic Influence on Risk Assessment of Road Traffic." In Lecture Notes in Mechanical Engineering, 561–67. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41468-3_47.

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Rhinehart, R. Russell, and Robert M. Bethea. "Risk." In Applied Engineering Statistics, 225–36. 2nd ed. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003222330-14.

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Liu, Ze-zhao, Hui-jia Wang, Juan-li Wang, and J. Huang. "Risk Analysis and Management Mechanism Innovation on Northwest China Urban Minority Floating Population—A Statistic Sample from City of Xi’an." In Proceedings of 2013 4th International Asia Conference on Industrial Engineering and Management Innovation (IEMI2013), 299–309. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40060-5_29.

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Rogers, Jamie. "Financial Statistics." In Strategy, Value and Risk, 73–82. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21978-9_4.

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Jia, Junbo. "Statistics of Motions and Loads." In Risk Engineering, 119–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-37003-8_10.

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Cox, Louis Anthony. "Statistical Risk Modeling." In Risk Analysis Foundations, Models, and Methods, 133–215. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0847-2_3.

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Faber, Michael Havbro. "Descriptive Statistics." In Topics in Safety, Risk, Reliability and Quality, 21–42. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-4056-3_3.

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Keener, Robert W. "Risk, Sufficiency, Completeness, and Ancillarity." In Theoretical Statistics, 39–59. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-93839-4_3.

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Damnjanovic, Ivan, and Kenneth Reinschmidt. "Statistical Project Control." In Risk, Systems and Decisions, 277–303. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-14251-3_12.

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Conference papers on the topic "Statistic risk"

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Dziadosz, Agnieszka, and Mariusz Rejment. "Risk assessment in construction project using statistic approach." In CENTRAL EUROPEAN SYMPOSIUM ON THERMOPHYSICS 2019 (CEST). AIP Publishing, 2019. http://dx.doi.org/10.1063/1.5114169.

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Borisenko, J. V. "The Statistic Model Of Suicide Risk Among Russian Students." In icCSBs 2019 - 8th Annual International Conference on Cognitive - Social, and Behavioural Sciences. Cognitive-Crcs, 2019. http://dx.doi.org/10.15405/epsbs.2019.12.02.26.

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Ker-tah, Hsu, Liu Weiling, and Yan Tzung-ming. "Grey clustering statistic, policyholder's risk attitude and purchase decision." In 2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009). IEEE, 2009. http://dx.doi.org/10.1109/gsis.2009.5408080.

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Gao, Cui-Juan, De-Yong Zhao, Wei-Min Ye, and Xiao Chen. "Notice of Retraction Risk assesment method based on concentrated numeric statistic matrix." In 2013 International Conference on Quality, Reliability, Risk, Maintenance and Safety Engineering (QR2MSE). IEEE, 2013. http://dx.doi.org/10.1109/qr2mse.2013.6625607.

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Yang Liu. "Operational statistic risk assessment for power systems under extreme weather conditions." In 10th International Conference on Advances in Power System Control, Operation & Management (APSCOM 2015). Institution of Engineering and Technology, 2015. http://dx.doi.org/10.1049/ic.2015.0292.

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Zheng, Yi, Qing-Xia Geng, and Rui He. "The application of control chart based on Bayesian Statistic in equipment maintenance quality control." In 2013 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE). IEEE, 2013. http://dx.doi.org/10.1109/qr2mse.2013.6625894.

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Mai, Songyan, Ji Zeng, Qi Feng, Renan Liu, and Yan Chen. "Risk Assessment of Ship Systems Based on Forward FTF Method." In ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/omae2019-95320.

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Abstract Ocean-going vessels sailing alone in the boundless sea often encounter various problems and pose a serious threat to the safety of the ship. According to statistic, many of these accidents are caused by problems such as aging equipment and lack of maintenance. After IMO issued mandatory regulations, China Classification Society (CCS) released Failure Mode and Impact Analysis Guide in 2017 (Guidance Notes GD16-2017), in connection with failure mode and impact analysis for ship equipment and systems. In this paper, based on a multi-purpose offshore carrier, the forward FTF (FMECA & FTA) method is adopted. The failure mode, effects and criticality analysis (FMECA) is conducted for the study on failure mode of ship system, including failure rate, cause and effect (probability and severity). Fault tree analysis (FTA) is to calculate and assess the risk of the ship system. Based on the forward FTF principle, Smart Captain, an operation and maintenance management system was developed for this ship. The system can identify the faults of the ship system and carry out different levels of alarms automatically, then a corresponding maintenance and operation instructions according to the equipment manual is given. By using Smart Captain, the crew member can carry out ship operation and maintenance efficiently safely.
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Zheng, Zhijie, Zhicheng Sha, and Lei Li. "Application of Interval Method in Reliability Analysis of Nuclear Plant Off-Site Power Supply." In 18th International Conference on Nuclear Engineering. ASMEDC, 2010. http://dx.doi.org/10.1115/icone18-29134.

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The loss of off-site power supply for nuclear power plants may lead to a core melt accident, with large potential risk. So the evaluation of loss of off-site power is important for the PSA (Probabilistic Safety Assessment). Uncertainty of the original parameters of electric grid components may be caused by the shortage of the statistical information, the approximation to model parameters or the statistic error. In order to deal with the uncertainty problem in electric grids, interval analysis method is introduced in this paper. The original reliability parameters that are changing in a certain range are treated with interval number. Thereby the uncertainty of the parameters can be calculated in the whole process of the probabilistic assessment. The proposed method has been tested on the reliability analysis evaluation of T power plant loss of off-site power. The results demonstrated the effectiveness and practical value of the interval analysis method.
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A Halim, Rahimah, M. Hatta Mhd Yusof, M. Hanafi M Khalid, Hao Xiang Wong, and M. Zarkashi Sulaiman. "Wait on Weather WOW Impact Trending in Malaysia Water: Comprehensive Data Analytics Led to Safe and Optimum Well Planning and Offshore Execution." In International Petroleum Technology Conference. IPTC, 2021. http://dx.doi.org/10.2523/iptc-21259-ms.

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Abstract Drilling operation in Malaysia are typically from offshore, thus offshore weather condition does contributed to the success or delay of a drilling operation. Wait on Weather (WOW) especially during monsoon season in Malaysia has impacted Operator's drilling operation, thus incurring additional cost to Operator. Monsoon season in Malaysia is typically from November to February every year. This paper will discuss and share the statistics of actual WOW happening from 2008 to 2019 in Malaysia water especially for jack-up rig (JUR) and tender assisted drilling rig (TADR) which are two common rigs in Malaysia water. The data was collected from one of the drilling operator in Malaysia. These data will be of assistance to Operator in better planning and executing drilling operation with the actual statistics as the risk factor. WOW is considered as non-productive time (NPT), thus NPT data gathering from Operators in Malaysia water were conducted. Data was then filtered to achieve the WOW data. WOW data was segregated between region in Malaysia which are Peninsular Malaysia (PM), Sabah (SB) and Sarawak (SK) as well as rig type, which are JUR and TADR. Distribution analysis were made to calculate the average and observe the maximum numbers of actual WOW occurrence. Further analysis was made to zoom into monsoon season in Malaysia which typically in November to February. 11 years data is generally good coverage for the analysis since it covers the up and down of oil and gas industry. Analysis was also done for both mob/demob and operation stage where it can be observed that WOW for mob/demob stage during monsoon season is significantly higher compared to operation stage. At the end of the analysis, the average or maximum numbers of WOW will be shared, and it will be used as recommendation for future projects to consider these figures as WOW risk factor and embed in the planning stage. This paper will help not only Operators in Malaysia water but the host authority on understanding the WOW risk factor during monsoon season. As WOW is not something that can be predicted, utilizing the standard results from actual statistic data for the past 11 years will assist engineers to incorporate the WOW risk factor during planning and execution stage. Rig and project sequencing can be optimized with understanding of WOW impact thus reducing the value leakage during operation due to WOW.
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De Poli, Gian Paolo, Carlo Frola, Massimo Gallizio, Luca Fattore, and Massimiliano Mattone. "Multidisciplinary Integration and Robustness Evaluation Applied to Low Pressure Turbine Casing Design." In ASME Turbo Expo 2006: Power for Land, Sea, and Air. ASMEDC, 2006. http://dx.doi.org/10.1115/gt2006-90464.

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In modern aerospace engineering design context one of the most important task is managing and simulate properly the effect of uncertainties on the response and performance of the system. In fact real engineering problems are characterised by random variations of material property, variation of loading conditions, manufacturing tolerances, etc. Different approaches have been developed by the research community to address uncertainties; while reliability methods primarily deal with probability of constraint satisfaction or violation, robust design methods have focused on the variation of system responses due to design parameters random variation. In this paper a robust design (RD) analysis of gas-turbine casing is performed in order to estimate how much uncertainties affect the life of the component. The RD analysis is performed in a multidisciplinary environment since the casing is subjected to thermo-mechanical loads. First thermal steady-state analysis has been performed changing randomly the boundary conditions (heat transfer coefficient and air temperature) and the temperature distribution on the casing is calculated. Then the structural analysis is performed changing geometrical dimensions on the base of defined tolerances and process capability. The result of the Monte Carlo analysis is a statistic distribution of the stress in the critical locations. This information is used to estimate the statistic distribution of the life in each critical location. The obtained result consents to evaluate the risk that some critical location exceeds the life margin limit.
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Reports on the topic "Statistic risk"

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Nelson, Gena. High Leverage Practices in Special Education Synthesis Coding Protocol. Boise State University, March 2021. http://dx.doi.org/10.18122/sped134.boisestate.

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The purpose of document is to provide readers with the coding protocol that authors used to code 76 meta-analyses focused on students with or at-risk of disabilities. All of the included meta-analyses provided a summary statistic related to at least one of the High Leverage Practices (HLPs; McLeskey et al., 2017). ). The purpose of the systematic review of meta-analyses was to provide an initial investigation of the evidence supporting the effectiveness of the HLPs for students with, or at-risk for, a disability. This code book contains variable names, code options, and code definitions related to basic study information (i.e., authors, year of publication, journal), the details of each study, participant demographics, HLPs included in each study, and summary statistics. The mean interrater reliability across all codes using this protocol was 88% (range across categories = 84%–97%)
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Einav, Liran, Amy Finkelstein, Raymond Kluender, and Paul Schrimpf. Beyond Statistics: The Economic Content of Risk Scores. Cambridge, MA: National Bureau of Economic Research, June 2015. http://dx.doi.org/10.3386/w21304.

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Saricks, C. L., R. G. Williams, and M. R. Hopf. Data base of accident and agricultural statistics for transportation risk assessment. Office of Scientific and Technical Information (OSTI), November 1989. http://dx.doi.org/10.2172/7171598.

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Uryasev, Stan, and Tyrrel R. Rockafellar. New Developments in Uncertainty: Linking Risk Management, Reliability, Statistics and Stochastic Optimization. Fort Belvoir, VA: Defense Technical Information Center, November 2014. http://dx.doi.org/10.21236/ada616353.

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Levitt, Steven, and Jack Porter. Estimating the Effect of Alcohol on Driver Risk Using Only Fatal Accident Statistics. Cambridge, MA: National Bureau of Economic Research, February 1999. http://dx.doi.org/10.3386/w6944.

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Mirel, Lisa, Cindy Zhang, Christine Cox, Ye Yeats, Félix Suad El Burai, and Golden Cordell. Comparative analysis of the National Health and Nutrition Examination Survey public-use and restricted-use linked mortality files. Centers for Disease Control and Prevention (U.S.), May 2021. http://dx.doi.org/10.15620/cdc:104744.

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"Objectives—Linking national survey data with administrative data sources enables researchers to conduct analyses that would not be possible with each data source alone. Recently, the Data Linkage Program at the National Center for Health Statistics (NCHS) released updated Linked Mortality Files, including the National Health and Nutrition Examination Survey data linked to the National Death Index mortality files. Two versions of the files were released: restricted-use files available through NCHS and Federal Statistical Research Data Centers and public-use files. To reduce the reidentification risk, statistical disclosure limitation methods were applied to the public-use files before they were released. This included limiting the amount of mortality information available and perturbing cause of death and follow-up time for select records. Methods—To assess the comparability of the restricted-use and public-use files, relative hazard ratios for all-cause and cause-specific mortality using Cox proportional hazards models were estimated and compared. Results—The comparative analysis found that the two data files yield similar descriptive and model results. Suggested citation: Mirel LB, Zhang C, Cox CS, Ye Y, El Burai Félix S, Golden C. Comparative analysis of the National Health and Nutrition Examination Survey public-use and restricted-use linked mortality files. National Health Statistics Reports; no 155. Hyattsville, MD: National Center for Health Statistics. 2021. DOI: https://doi.org/10.15620/cdc:104744. CS323656 nhsr155-508.pdf"
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Kaplow, Louis. The Value of a Statistical Life and the Coefficient of Relative Risk Aversion. Cambridge, MA: National Bureau of Economic Research, July 2003. http://dx.doi.org/10.3386/w9852.

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Burnside, A. Craig. Empirical Asset Pricing and Statistical Power in the Presence of Weak Risk Factors. Cambridge, MA: National Bureau of Economic Research, August 2007. http://dx.doi.org/10.3386/w13357.

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Pizarro, Rodrigo, Raúl Delgado, Huáscar Eguino, and Aloisio Lopes Pereira. Climate Change Public Budget Tagging: Connections across Financial and Environmental Classification Systems. Inter-American Development Bank, January 2021. http://dx.doi.org/10.18235/0003021.

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Identifying and evaluating climate expenditures in the public sector, known as budget tagging, has generated increasing attention from multiple stakeholders, not only to assess the governments climate change policy, but also to monitor fiscal risks associated with increasing and unpredictable climate change impacts. This paper explores the issues raised by climate change budget tagging in the context of a broader discussion on the connections with fiscal and environmental statistical classification systems. It argues that, for climate change budget tagging efforts to be successful, the definitions and classifications of climate change expenditures must be consistent with statistical standards currently in use, such as the Government Finance Statistics Framework and the System of National Accounts.
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Mukherjee, Sayan, Partha Niyogi, Tomaso Poggio, and Ryan Rifkin. Statistical Learning: Stability is Sufficient for Generalization and Necessary and Sufficient for Consistency of Empirical Risk Minimization. Fort Belvoir, VA: Defense Technical Information Center, January 2004. http://dx.doi.org/10.21236/ada459857.

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