Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 11 of 11 for “"Skew normal"”.
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Skew Normal Bayesian Asset Allocation
… a Bayesian asset allocation problem based on the skew-normal distribution assumption and extends the Bayesian asset allocation model obtained by assuming hidden truncation skew-normal returns. Hidden truncation model provides a flexible family of skewed alternatives to the classical k dimensional …
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Two generalizations of the skew-normal distribution and two variants of McCarthy's theorem
… The first and major part is concerned with the skew-normal distribution, introduced by Azzalini (1985) [6], while the second one is connected with the scoring rules. In part one the problem of finding confidence intervals for the skewness parameter of the skew-normal distribution is addressed. …
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Modelling skewness in Financial data
The first systematic analysis of the skew-normal distribution in a scalar case is done by Azzalini (1985). Unlike most of the skewed distributions, the skew-normal distribution allows continuity of the passage from the normal distribution to the skew-normal distribution and is mathematically …
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Topics in dimension reduction and missing data in statistical discrimination.
… discriminant analysis for multiple multivariate skew-normal populations. First, we define the multivariate skew-normal distribution and give several applications of its use. We also provide marginal and conditional properties of the MSN random vector. Then, we state and prove several lemmas used …
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Bayesian Measurement Error Modeling
<p>A mixture measurement error model built upon skew normal distributions and normal distributions is developed to evaluate various impacts of measurement errors to parameter inferences in logistic regressions. Data generated from survey questionnaires are usually error contaminated. We consider …
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Four Essays on Dynamic Panel Models
… technical efficiency framework allows for skew-Normal errors. Simulation studies support all theoretical results, with confidence sets that are level correct with good coverage properties, even for asymmetric confidence regions.
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The Spectral Model of Grain Boundary Solute Segregation
… is found to be captured accurately with a skew-normal function. Second, we outline a thermodynamic segregation isotherm that incorporates this spectrum, and employ it to study the effect of such a spectrum on predictions of the equilibrium GB segregation state. Third, we develop a machine …
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Characterization of exoplanetary systems combining transit timing techniques and radial velocities: From secular perturbations to resonant chains
… Myr) multi-planet system V1298 Tau, applying a Skew-Normal fitting method to model the cross-correlation function (CCF) and mitigate stellar activity in nearly 400 HARPS-N spectra. Coupling this RV extraction with photodynamical modeling of TTVs+RVs and Gaussian process regression will enable a …
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Nonparametric Methods for Analysis and Modeling of Complex Multivariate Distributions
… the number of cell clusters; the hierarchical skew normal kernels allow flexibility in the shapes of the cell subsets and cross-sample variation in their locations; and finally the ``coarsening'' strategy makes inference robust to small departures from the model, a feature that becomes crucial …
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Interpreting Ancient Climate Signals from Sedimentary Archives of Lake Bosumtwi, Ghana
… presents a new nonparametric method called the skew normal distribution deconvolution (SNDD) that parses a sample GSD into one or more component subpopulations, each of which can be fully quantified by a parameter set (C_i,ξ_i,ω_i^2 〖,α 〗_i) of a skewed normal distribution (SND). A key advance …
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Understanding blood pressure dynamics in the South African population: a latent variables approach to the analysis and comparison of data from multiple surveys
… general framework, multiple group modelling, normal‐censored regression, mixture analysis with skew‐normal distributions and the use of additional parameters and phantom variables) represent a viable and advantageous alternative to current methods of comparative analysis of blood pressure …