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Showing 1 to 10 of 10 for “"multiple hypothesis testing"”.

  1. Composite Likelihood: Multiple Comparisons and Non-Standard Conditions in Hypothesis Testing

    … reducing the dimension. We study the problem of multiple hypothesis testing for multidimensional clustered data. The problem of multiple comparisons is common in many applications. We propose to construct multiple comparisons procedures based on composite likelihood statistics. The simultaneous …

    york Repository record for Composite Likelihood: Multiple Comparisons and Non-Standard Conditions in Hypothesis Testing (opens in a new tab)

  2. New Results on the False Discovery Rate

    … used in a wide variety of applications involving multiple hypothesis testing. There are two approaches to control the FDR - the fixed error rate approach of Benjamini and Hochberg (BH, 1995) where a rejection region is determined with the FDR below a fixed level and the estimation based approach …

    temple Repository record for New Results on the False Discovery Rate (opens in a new tab)

  3. Identification of Deleterious and Disease Alleles in a General Population and Preterm Labor Patients

    … SNPs can be explained by false positives due to multiple hypothesis testing, violation of evolutionary model assumptions, recent gene duplication and relaxation of selective constraints on biological processes. Next, by applying the likelihood ratio test to a general human population, I find that …

    wustl Repository record for Identification of Deleterious and Disease Alleles in a General Population and Preterm Labor Patients (opens in a new tab)

  4. A Robust Dynamic State and Parameter Estimation Framework for Smart Grid Monitoring and Control

    … outliers. A reformulation of the GM-UKF with multiple hypothesis testing further enables it to handle structural outliers. However, the GM-UKF may yield biased state estimates in presence of large system uncertainties. To this end, the H-infinity UKF that relies on robust control theory is …

    vt Repository record for A Robust Dynamic State and Parameter Estimation Framework for Smart Grid Monitoring and Control (opens in a new tab)

  5. Sensitivity to Distributional Assumptions in Estimation of the ODP Thresholding Function

    … 2005) builds on the framework of Neyman-Pearson hypothesis testing to optimally test thousands of hypotheses simultaneously. The method relies on the assumption of normally distributed data; however, many applications of this method will violate this assumption. This thesis investigates the …

    byu Repository record for Sensitivity to Distributional Assumptions in Estimation of the ODP Thresholding Function (opens in a new tab)

  6. Sequential anomaly detection under sampling constraints

    Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2025-05-01

    uiuc Repository record for Sequential anomaly detection under sampling constraints (opens in a new tab)

  7. Topics on statistical design and analysis of cDNA microarray experiment

    … test simultaneously. Since it is a case of multiple hypothesis testing, some kind of adjustment should be made to the p-values resulted from the statistical test. Lots of multiple testing error rates, such as FDR, lFDR and pFDR have been proposed to address this issue. A key related problem …

    glasgow Repository record for Topics on statistical design and analysis of cDNA microarray experiment (opens in a new tab)

  8. Locally Adaptive Protocols for Quantum State Discrimination

    … is additionally highly effective for the task of multiple quantum hypothesis testing. </p><p>Quantum hypothesis testing consists of finding the quantum measurement which allows one to discriminate with minimal error between $m$ possible states $\{\rho_{k}\}|_{k=1}^{m}$ of a quantum system with …

    duke Repository record for Locally Adaptive Protocols for Quantum State Discrimination (opens in a new tab)

  9. New methods for econometric inference

    … effective and practical econometric methods for testing this prediction in empirical analysis. Chapter 1 develops a general nonparametric framework for testing monotonicity of a regression function. Using this framework, a broad class of new tests is introduced, which gives an empirical …

    mit Repository record for New methods for econometric inference (opens in a new tab)

  10. Early Undernutrition and Unmet Learning Needs: Exploring Relationships between Stunting, Cognition, and Teacher Perceptions of Early Grade Learning in Ghana

    … for changes in standard error associated with multiple hypothesis testing, no statistically significant differences were found between stunted and non-stunted groups for the cognitive domains of visuospatial reasoning, visual selective attention, processing speed, short term memory, working …

    cambridge Repository record for Early Undernutrition and Unmet Learning Needs: Exploring Relationships between Stunting, Cognition, and Teacher Perceptions of Early Grade Learning in Ghana (opens in a new tab)