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Showing 1 to 17 of 17 for “"exact distribution"”.

  1. Comparing k Population Means with No Assumption about the Variances

    … for k=2. We propose a method that uses the exact distribution of the likelihood ratio (test) statistic. The data is used to estimate this exact distribution to obtain an estimated critical value or an estimated p-value.</p>

    gsu Repository record for Comparing k Population Means with No Assumption about the Variances (opens in a new tab)

  2. ΜΕΓΙΣΤΟ ΜΗΚΟΣ ΡΟΗΣ ΕΠΙΤΥΧΙΩΝ ΚΑΙ ΠΟΛΥΩΝΥΜΑ ΤΥΠΟΥ-FIBONACCI

    … OF ORDER K. WE INTRODUCE AND STUDY A NEW DISTRIBUTION, THE BINOMIAL DISTRIBUTION OF ORDER K AND DERIVE THE EXACT DISTRIBUTION OF IT. APPLICATIONS OF THE RANDOM VARIABLES WHICH WE STUDY ARE GIVEN IN RELIABILITY OF CONSECUTIVE-K-OUT-OF-N F SYSTEMS.WE ALSO GIVE THE RELIABILITY OF A …

    greece Repository record for ΜΕΓΙΣΤΟ ΜΗΚΟΣ ΡΟΗΣ ΕΠΙΤΥΧΙΩΝ ΚΑΙ ΠΟΛΥΩΝΥΜΑ ΤΥΠΟΥ-FIBONACCI (opens in a new tab)

  3. A study on improving the performance of control charts under non-normal distributions

    … that the monitoring statistic follows a normal distribution. While the normality assumption is invalid in many cases, the traditional 3-sigma limits may become inappropriate. In this thesis, we have raised two approaches to solve the non-normality problem. The first approach is based on the …

    nus Repository record for A study on improving the performance of control charts under non-normal distributions (opens in a new tab)

  4. Weak signal identification and inference in penalized model selection

    … provide signal's inference method based on the exact distribution of penalized estimator. The finite sample distribution is quite different from its asymptotic counterpart, which can be highly non-normal with a point mass at zero. Numerical studies indicate that the density-based approach works …

    uiuc Repository record for Weak signal identification and inference in penalized model selection (opens in a new tab)

  5. Inference in Ising models by graph neural networks with structural features

    … and maximum-a-posteriori (MAP) inference. Exact inference on PGMs is intractable, hence approximation algorithms, such as belief propagation, are proposed for practical applications. Recently Graphical Neural Networks (GNNs) are shown to outperform BP on small-scale loopy graphs. GNN …

    uiuc Repository record for Inference in Ising models by graph neural networks with structural features (opens in a new tab)

  6. Estimation of the strength of a radioactive source

    … rapid so that the usual assumption of a Poisson distribution of counts is not applicable. We distinguish two main cases according as the background radiation is small or large. In the former case the common procedure of simply subtracting off a constant background radiation is adequate. If the …

    vt Repository record for Estimation of the strength of a radioactive source (opens in a new tab)

  7. Estimating the Hausdorff dimension

    … or its estimate, using an occupancy model. The exact distribution of the estimator is also derived. Applications of the theory to various fields are presented. For example, I find that from the point of view of dimension, the logarithms of stock prices behave consistently with the classical …

    vt Repository record for Estimating the Hausdorff dimension (opens in a new tab)

  8. Contributions to Profile Monitoring and Multivariate Statistical Process Control

    … monitoring and 2) an improved approximate distribution for the T² statistic based on the successive differences covariance matrix estimator. Part 1: Nonlinear Profile Monitoring In an increasing number of cases the quality of a product or process cannot adequately be represented by the …

    vt Repository record for Contributions to Profile Monitoring and Multivariate Statistical Process Control (opens in a new tab)

  9. Multiagent planning with Bayesian nonparametric asymptotics

    … allocation under uncertainty by allowing exact distribution propagation instead of sampling, and provides an analytic solution time/quality tradeoff for system designers. The second contribution is the Dynamic Means algorithm, a novel clustering method based upon Bayesian nonparametrics …

    mit Repository record for Multiagent planning with Bayesian nonparametric asymptotics (opens in a new tab)

  10. Development of Monte Carlo models of a gamma-ray nondestructive assay system for nuclear material control and accountability

    … in certain scenarios due to the complex distributions and compositions samples can exhibit. Monte Carlo models of a high-purity germanium (HPGe) gamma-ray detector used for assaying plutonium were developed and benchmarked to simulate two difficult measurement scenarios often faced at Los …

    tdl Repository record for Development of Monte Carlo models of a gamma-ray nondestructive assay system for nuclear material control and accountability (opens in a new tab)

  11. Nonparametric procedures for process control when the control value is not specified

    … (CUSUM chart). In designing a control chart, the exact distribution of the observations, e.g. normal distribution, is usually assumed to be known. But, when there is not sufficient information in determining the distribution, nonparametric procedures are appropriate. In such cases, the control …

    vt Repository record for Nonparametric procedures for process control when the control value is not specified (opens in a new tab)

  12. Analytic Results for Hopping Models with Excluded Volume Constraint

    … by the Brownian vacancy. The probability distributions for its displacement and for the number of steps taken, after n-steps of the vacancy, are derived. Neither is a Gaussian! We also show that the only nontrivial dimension where the walk is recurrent is d=2. As an application, we compute …

    vt Repository record for Analytic Results for Hopping Models with Excluded Volume Constraint (opens in a new tab)

  13. Maximum-likelihood-based confidence regions and hypothesis tests for selected statistical models.

    … least squares approach (OLS). However, the exact distribution of the SUR estimator is complex and does not yield easily-formed confidence regions of a coefficient parameter. Therefore, one can apply maximum likelihood (ML) asymptotic-based methods to construct a confidence region. Here, we …

    baylor Repository record for Maximum-likelihood-based confidence regions and hypothesis tests for selected statistical models. (opens in a new tab)

  14. Haplotype-Based Association Studies: Approaches to Current Challenges

    … thesis involves the uncertainty regarding the exact distribution of the likelihood ratio test (LRT) statistic for haplotype-based association tests in which many of the haplotype frequency estimates are zero or very small. By simulating datasets with known haplotype frequencies and comparing …

    rockefeller Repository record for Haplotype-Based Association Studies: Approaches to Current Challenges (opens in a new tab)

  15. Comparison of Exact Unconditional Methods for the Difference of Two Binomial Proportions

    Exact tests based upon the difference of two independent binomial proportions are popularly used and are especially suited for studies with small to moderate sample sizes. In the context of testing for superiority and noninferiority, we apply the confidence region p-value method (Berger and Boos, …

    ncsu Repository record for Comparison of Exact Unconditional Methods for the Difference of Two Binomial Proportions (opens in a new tab)

  16. Probabilistic arithmetic automata : applications of a stochastic computational framework in biological sequence analysis

    … the computational framework to calculate the exact distribution of the value resulting from those operations. For instance, the PAA framework can be used to compute the expected molecular mass of a peptide resulting from the cleavage reaction of a protease. Moreover, we show that the framework …

    bielefeld Repository record for Probabilistic arithmetic automata : applications of a stochastic computational framework in biological sequence analysis (opens in a new tab)

  17. Stochastic Geometry for Vehicular Networks

    … of interfering nodes and also the underlying distribution of lines. We carefully handle these constraints using various fundamental distance properties of the PLCP and derive the exact expression for the coverage probability. Third, building further on the above mentioned works, we consider a …

    vt Repository record for Stochastic Geometry for Vehicular Networks (opens in a new tab)