Mostrando recursos 1 - 20 de 137

  1. Focusing on regions of interest in forecast evaluation

    Holzmann, Hajo; Klar, Bernhard
    Often, interest in forecast evaluation focuses on certain regions of the whole potential range of the outcome, and forecasts should mainly be ranked according to their performance within these regions. A prime example is risk management, which relies on forecasts of risk measures such as the value-at-risk or the expected shortfall, and hence requires appropriate loss distribution forecasts in the tails. Further examples include weather forecasts with a focus on extreme conditions, or forecasts of environmental variables such as ozone with a focus on concentration levels with adverse health effects. ¶ In this paper, we show how weighted scoring rules...

  2. Focusing on regions of interest in forecast evaluation

    Holzmann, Hajo; Klar, Bernhard
    Often, interest in forecast evaluation focuses on certain regions of the whole potential range of the outcome, and forecasts should mainly be ranked according to their performance within these regions. A prime example is risk management, which relies on forecasts of risk measures such as the value-at-risk or the expected shortfall, and hence requires appropriate loss distribution forecasts in the tails. Further examples include weather forecasts with a focus on extreme conditions, or forecasts of environmental variables such as ozone with a focus on concentration levels with adverse health effects. ¶ In this paper, we show how weighted scoring rules...

  3. Focusing on regions of interest in forecast evaluation

    Holzmann, Hajo; Klar, Bernhard
    Often, interest in forecast evaluation focuses on certain regions of the whole potential range of the outcome, and forecasts should mainly be ranked according to their performance within these regions. A prime example is risk management, which relies on forecasts of risk measures such as the value-at-risk or the expected shortfall, and hence requires appropriate loss distribution forecasts in the tails. Further examples include weather forecasts with a focus on extreme conditions, or forecasts of environmental variables such as ozone with a focus on concentration levels with adverse health effects. ¶ In this paper, we show how weighted scoring rules...

  4. Statistical downscaling for future extreme wave heights in the North Sea

    Towe, Ross; Eastoe, Emma; Tawn, Jonathan; Jonathan, Philip
    For safe offshore operations, accurate knowledge of the extreme oceanographic conditions is required. We develop a multi-step statistical downscaling algorithm using data from a low resolution global climate model (GCM) and local-scale hindcast data to make predictions of the extreme wave climate in the next 50-year period at locations in the North Sea. The GCM is unable to produce wave data accurately so instead we use its 3-hourly wind speed and direction data. By exploiting the relationships between wind characteristics and wave heights, a downscaling approach is developed to relate the large and local-scale data sets, and hence future changes...

  5. Statistical downscaling for future extreme wave heights in the North Sea

    Towe, Ross; Eastoe, Emma; Tawn, Jonathan; Jonathan, Philip
    For safe offshore operations, accurate knowledge of the extreme oceanographic conditions is required. We develop a multi-step statistical downscaling algorithm using data from a low resolution global climate model (GCM) and local-scale hindcast data to make predictions of the extreme wave climate in the next 50-year period at locations in the North Sea. The GCM is unable to produce wave data accurately so instead we use its 3-hourly wind speed and direction data. By exploiting the relationships between wind characteristics and wave heights, a downscaling approach is developed to relate the large and local-scale data sets, and hence future changes...

  6. Statistical downscaling for future extreme wave heights in the North Sea

    Towe, Ross; Eastoe, Emma; Tawn, Jonathan; Jonathan, Philip
    For safe offshore operations, accurate knowledge of the extreme oceanographic conditions is required. We develop a multi-step statistical downscaling algorithm using data from a low resolution global climate model (GCM) and local-scale hindcast data to make predictions of the extreme wave climate in the next 50-year period at locations in the North Sea. The GCM is unable to produce wave data accurately so instead we use its 3-hourly wind speed and direction data. By exploiting the relationships between wind characteristics and wave heights, a downscaling approach is developed to relate the large and local-scale data sets, and hence future changes...

  7. Estimating the number of casualties in the American Indian war: A Bayesian analysis using the power law distribution

    Gillespie, Colin S.
    The American Indian War lasted over one hundred years, and is a major event in the history of North America. As expected, since the war commenced in late eighteenth century, casualty records surrounding this conflict contain numerous sources of error, such as rounding and counting. Additionally, while major battles such as the Battle of the Little Bighorn were recorded, many smaller skirmishes were completely omitted from the records. Over the last few decades, it has been observed that the number of casualties in major conflicts follows a power law distribution. This paper places this observation within the Bayesian paradigm, enabling...

  8. Estimating the number of casualties in the American Indian war: A Bayesian analysis using the power law distribution

    Gillespie, Colin S.
    The American Indian War lasted over one hundred years, and is a major event in the history of North America. As expected, since the war commenced in late eighteenth century, casualty records surrounding this conflict contain numerous sources of error, such as rounding and counting. Additionally, while major battles such as the Battle of the Little Bighorn were recorded, many smaller skirmishes were completely omitted from the records. Over the last few decades, it has been observed that the number of casualties in major conflicts follows a power law distribution. This paper places this observation within the Bayesian paradigm, enabling...

  9. Estimating the number of casualties in the American Indian war: A Bayesian analysis using the power law distribution

    Gillespie, Colin S.
    The American Indian War lasted over one hundred years, and is a major event in the history of North America. As expected, since the war commenced in late eighteenth century, casualty records surrounding this conflict contain numerous sources of error, such as rounding and counting. Additionally, while major battles such as the Battle of the Little Bighorn were recorded, many smaller skirmishes were completely omitted from the records. Over the last few decades, it has been observed that the number of casualties in major conflicts follows a power law distribution. This paper places this observation within the Bayesian paradigm, enabling...

  10. Automatic matching of bullet land impressions

    Hare, Eric; Hofmann, Heike; Carriquiry, Alicia
    In 2009, the National Academy of Sciences published a report questioning the scientific validity of many forensic methods including firearm examination. Firearm examination is a forensic tool used to help the court determine whether two bullets were fired from the same gun barrel. During the firing process, rifling, manufacturing defects, and impurities in the barrel create striation marks on the bullet. Identifying these striation markings in an attempt to match two bullets is one of the primary goals of firearm examination. We propose an automated framework for the analysis of the 3D surface measurements of bullet land impressions, which transcribes...

  11. Automatic matching of bullet land impressions

    Hare, Eric; Hofmann, Heike; Carriquiry, Alicia
    In 2009, the National Academy of Sciences published a report questioning the scientific validity of many forensic methods including firearm examination. Firearm examination is a forensic tool used to help the court determine whether two bullets were fired from the same gun barrel. During the firing process, rifling, manufacturing defects, and impurities in the barrel create striation marks on the bullet. Identifying these striation markings in an attempt to match two bullets is one of the primary goals of firearm examination. We propose an automated framework for the analysis of the 3D surface measurements of bullet land impressions, which transcribes...

  12. Automatic matching of bullet land impressions

    Hare, Eric; Hofmann, Heike; Carriquiry, Alicia
    In 2009, the National Academy of Sciences published a report questioning the scientific validity of many forensic methods including firearm examination. Firearm examination is a forensic tool used to help the court determine whether two bullets were fired from the same gun barrel. During the firing process, rifling, manufacturing defects, and impurities in the barrel create striation marks on the bullet. Identifying these striation markings in an attempt to match two bullets is one of the primary goals of firearm examination. We propose an automated framework for the analysis of the 3D surface measurements of bullet land impressions, which transcribes...

  13. Modeling node incentives in directed networks

    Chakrabarti, Deepayan
    Twitter is a popular medium for individuals to gather information and express opinions on topics of interest to them. By understanding who is interested in what topics, we can gauge the public mood, especially during periods of polarization such as elections. However, while the total volume of tweets may be huge, many people tweet rarely, and tweets are short and often noisy. Hence, directly inferring topics from tweets is both complicated and difficult to scale. Instead, the network structure of Twitter (who tweets at whom, who follows whom) can telegraph the interests of Twitter users. We propose the Producer-Consumer Model...

  14. Modeling node incentives in directed networks

    Chakrabarti, Deepayan
    Twitter is a popular medium for individuals to gather information and express opinions on topics of interest to them. By understanding who is interested in what topics, we can gauge the public mood, especially during periods of polarization such as elections. However, while the total volume of tweets may be huge, many people tweet rarely, and tweets are short and often noisy. Hence, directly inferring topics from tweets is both complicated and difficult to scale. Instead, the network structure of Twitter (who tweets at whom, who follows whom) can telegraph the interests of Twitter users. We propose the Producer-Consumer Model...

  15. Modeling node incentives in directed networks

    Chakrabarti, Deepayan
    Twitter is a popular medium for individuals to gather information and express opinions on topics of interest to them. By understanding who is interested in what topics, we can gauge the public mood, especially during periods of polarization such as elections. However, while the total volume of tweets may be huge, many people tweet rarely, and tweets are short and often noisy. Hence, directly inferring topics from tweets is both complicated and difficult to scale. Instead, the network structure of Twitter (who tweets at whom, who follows whom) can telegraph the interests of Twitter users. We propose the Producer-Consumer Model...

  16. Point process models for spatio-temporal distance sampling data from a large-scale survey of blue whales

    Yuan, Yuan; Bachl, Fabian E.; Lindgren, Finn; Borchers, David L.; Illian, Janine B.; Buckland, Stephen T.; Rue, Håvard; Gerrodette, Tim
    Distance sampling is a widely used method for estimating wildlife population abundance. The fact that conventional distance sampling methods are partly design-based constrains the spatial resolution at which animal density can be estimated using these methods. Estimates are usually obtained at survey stratum level. For an endangered species such as the blue whale, it is desirable to estimate density and abundance at a finer spatial scale than stratum. Temporal variation in the spatial structure is also important. We formulate the process generating distance sampling data as a thinned spatial point process and propose model-based inference using a spatial log-Gaussian Cox...

  17. Point process models for spatio-temporal distance sampling data from a large-scale survey of blue whales

    Yuan, Yuan; Bachl, Fabian E.; Lindgren, Finn; Borchers, David L.; Illian, Janine B.; Buckland, Stephen T.; Rue, Håvard; Gerrodette, Tim
    Distance sampling is a widely used method for estimating wildlife population abundance. The fact that conventional distance sampling methods are partly design-based constrains the spatial resolution at which animal density can be estimated using these methods. Estimates are usually obtained at survey stratum level. For an endangered species such as the blue whale, it is desirable to estimate density and abundance at a finer spatial scale than stratum. Temporal variation in the spatial structure is also important. We formulate the process generating distance sampling data as a thinned spatial point process and propose model-based inference using a spatial log-Gaussian Cox...

  18. Point process models for spatio-temporal distance sampling data from a large-scale survey of blue whales

    Yuan, Yuan; Bachl, Fabian E.; Lindgren, Finn; Borchers, David L.; Illian, Janine B.; Buckland, Stephen T.; Rue, Håvard; Gerrodette, Tim
    Distance sampling is a widely used method for estimating wildlife population abundance. The fact that conventional distance sampling methods are partly design-based constrains the spatial resolution at which animal density can be estimated using these methods. Estimates are usually obtained at survey stratum level. For an endangered species such as the blue whale, it is desirable to estimate density and abundance at a finer spatial scale than stratum. Temporal variation in the spatial structure is also important. We formulate the process generating distance sampling data as a thinned spatial point process and propose model-based inference using a spatial log-Gaussian Cox...

  19. Semiparametric covariate-modulated local false discovery rate for genome-wide association studies

    Zablocki, Rong W.; Levine, Richard A.; Schork, Andrew J.; Xu, Shujing; Wang, Yunpeng; Fan, Chun C.; Thompson, Wesley K.
    While genome-wide association studies (GWAS) have discovered thousands of risk loci for heritable disorders, so far even very large meta-analyses have recovered only a fraction of the heritability of most complex traits. Recent work utilizing variance components models has demonstrated that a larger fraction of the heritability of complex phenotypes is captured by the additive effects of SNPs than is evident only in loci surpassing genome-wide significance thresholds, typically set at a Bonferroni-inspired $p\le5\times10^{-8}$. Procedures that control false discovery rate can be more powerful, yet these are still under-powered to detect the majority of nonnull effects from GWAS. The current...

  20. Semiparametric covariate-modulated local false discovery rate for genome-wide association studies

    Zablocki, Rong W.; Levine, Richard A.; Schork, Andrew J.; Xu, Shujing; Wang, Yunpeng; Fan, Chun C.; Thompson, Wesley K.
    While genome-wide association studies (GWAS) have discovered thousands of risk loci for heritable disorders, so far even very large meta-analyses have recovered only a fraction of the heritability of most complex traits. Recent work utilizing variance components models has demonstrated that a larger fraction of the heritability of complex phenotypes is captured by the additive effects of SNPs than is evident only in loci surpassing genome-wide significance thresholds, typically set at a Bonferroni-inspired $p\le5\times10^{-8}$. Procedures that control false discovery rate can be more powerful, yet these are still under-powered to detect the majority of nonnull effects from GWAS. The current...

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