Revista Colombiana de Estadistica, ISSN 0120-1751, 2017, Volume 40, Issue 1, pp. 45 - 64

Journal Article

Revista Colombiana de Estadistica, ISSN 0120-1751, 2010, Volume 33, Issue 1, pp. 1 - 11

Journal Article

Bayesian Analysis, ISSN 1936-0975, 2006, Volume 1, Issue 3, pp. 515 - 534

Various noninformative prior distributions have been suggested for scale parameters in hierarchical models. We construct a new folded-noncentral-t family of...

Conditional conjugacy | Hierarchical model | Bayesian inference | Noninformative prior distribution | Half-t distribution | Folded-noncentral-t distribution | Multilevel model | Weakly informative prior distribution | conditional conjugacy | multilevel model | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | noninformative prior distribution | folded-noncentral-t distribution | weakly informative prior distribution | STATISTICS & PROBABILITY | half-t distribution | hierarchical model

Conditional conjugacy | Hierarchical model | Bayesian inference | Noninformative prior distribution | Half-t distribution | Folded-noncentral-t distribution | Multilevel model | Weakly informative prior distribution | conditional conjugacy | multilevel model | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | noninformative prior distribution | folded-noncentral-t distribution | weakly informative prior distribution | STATISTICS & PROBABILITY | half-t distribution | hierarchical model

Journal Article

Journal of the Royal Statistical Society. Series B (Statistical Methodology), ISSN 1369-7412, 1/2003, Volume 65, Issue 2, pp. 367 - 389

A fairly general procedure is studied to perturb a multivariate density satisfying a weak form of multivariate symmetry, and to generate a whole set of...

Gaussian distributions | Degrees of freedom | Scalars | Mathematical independent variables | Inference | Random variables | Steels | Mathematical expressions | T distribution | Distribution functions | Asymmetry | Elliptical distributions | Quadratic forms | Multivariate t‐distribution | Skewness | Central symmetry | Healy's plot | Skew normal distribution | Multivariate t-distribution | NORMAL RANDOM VECTORS | elliptical distributions | REGRESSION-MODELS | quadratic forms | STATISTICS & PROBABILITY | asymmetry | skewness | QUADRATIC-FORMS | central symmetry | skew normal distribution | multivariate t-distribution | Statistics - Methodology

Gaussian distributions | Degrees of freedom | Scalars | Mathematical independent variables | Inference | Random variables | Steels | Mathematical expressions | T distribution | Distribution functions | Asymmetry | Elliptical distributions | Quadratic forms | Multivariate t‐distribution | Skewness | Central symmetry | Healy's plot | Skew normal distribution | Multivariate t-distribution | NORMAL RANDOM VECTORS | elliptical distributions | REGRESSION-MODELS | quadratic forms | STATISTICS & PROBABILITY | asymmetry | skewness | QUADRATIC-FORMS | central symmetry | skew normal distribution | multivariate t-distribution | Statistics - Methodology

Journal Article

Scandinavian Journal of Statistics, ISSN 0303-6898, 6/2005, Volume 32, Issue 2, pp. 159 - 188

This paper provides an introductory overview of a portion of distribution theory which is currently under intense development. The starting point of this topic...

Economic models | Gaussian distributions | Mathematical independent variables | Inference | Stochastic models | Regression analysis | Random variables | Skewed distribution | Distribution functions | T distribution | selective sampling | heavy tails | graphical models | flexible parametric family | stochastic frontier models | skew‐elliptical distribution | skew‐t distribution | hidden truncation model | skew‐normal distribution | Skew-? distribution | Flexible parametric family | Graphical models | Stochastic frontier models | Selective sampling | Heavy tails | Hidden truncation model | Skew-normal distribution | Skew-elliptical distribution | TESTS | skew-t distribution | skew-elliptical distribution | skew-normal distribution | T-DISTRIBUTION | REPRESENTATION | STATISTICS & PROBABILITY | INFERENCE | NORMAL RANDOM VECTORS | MODELS | QUADRATIC-FORMS | MOMENTS

Economic models | Gaussian distributions | Mathematical independent variables | Inference | Stochastic models | Regression analysis | Random variables | Skewed distribution | Distribution functions | T distribution | selective sampling | heavy tails | graphical models | flexible parametric family | stochastic frontier models | skew‐elliptical distribution | skew‐t distribution | hidden truncation model | skew‐normal distribution | Skew-? distribution | Flexible parametric family | Graphical models | Stochastic frontier models | Selective sampling | Heavy tails | Hidden truncation model | Skew-normal distribution | Skew-elliptical distribution | TESTS | skew-t distribution | skew-elliptical distribution | skew-normal distribution | T-DISTRIBUTION | REPRESENTATION | STATISTICS & PROBABILITY | INFERENCE | NORMAL RANDOM VECTORS | MODELS | QUADRATIC-FORMS | MOMENTS

Journal Article

6.
Full Text
A Dynamic Multivariate Heavy-Tailed Model for Time-Varying Volatilities and Correlations

Journal of Business & Economic Statistics, ISSN 0735-0015, 10/2011, Volume 29, Issue 4, pp. 552 - 563

We propose a new class of observation-driven time-varying parameter models for dynamic volatilities and correlations to handle time series from heavy-tailed...

Multivariate Student t distribution | Copula | Dynamic dependence | Economic models | Time series models | Statistical discrepancies | Correlations | Matrices | Recursion | Covariance matrices | Parametric models | T distribution | Forecasting models | AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY | STATISTICS & PROBABILITY | SOCIAL SCIENCES, MATHEMATICAL METHODS | ECONOMICS | STOCHASTIC VOLATILITY | GARCH MODEL | HETEROSKEDASTICITY | Models | Correlation (Statistics) | Multivariate analysis | Volatility (Finance)

Multivariate Student t distribution | Copula | Dynamic dependence | Economic models | Time series models | Statistical discrepancies | Correlations | Matrices | Recursion | Covariance matrices | Parametric models | T distribution | Forecasting models | AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY | STATISTICS & PROBABILITY | SOCIAL SCIENCES, MATHEMATICAL METHODS | ECONOMICS | STOCHASTIC VOLATILITY | GARCH MODEL | HETEROSKEDASTICITY | Models | Correlation (Statistics) | Multivariate analysis | Volatility (Finance)

Journal Article

Scandinavian Journal of Statistics, ISSN 0303-6898, 03/2017, Volume 44, Issue 1, pp. 21 - 45

Skew‐symmetric families of distributions such as the skew‐normal and skew‐t represent supersets of the normal and t distributions, and they exhibit richer...

angular density, asymptotic independence, extremal coefficient, extreme values, max‐stable distribution, non‐central extended skew‐t distribution, non‐stationarity, skew‐normal distribution, skew‐normal process, skew‐t distribution | angular density, asymptotic independence, extremal coefficient, extreme values, max-stable distribution, non-central extended skew-t distribution, non-stationarity, skew-normal distribution, skew-normal process, skew-t distribution | FIELDS | max-stable distribution | skew-t distribution | STATISTICS | skew-normal distribution | REPRESENTATION | STATISTICS & PROBABILITY | NORMAL DISTRIBUTIONS | non-central extended skew-t distribution | non-stationarity | extreme values | angular density | extremal coefficient | VALUES | MAX-STABLE PROCESSES | skew-normal process | asymptotic independence | MULTIVARIATE EXTREMES | Studies | Normal distribution | Statistical analysis | Covariance | Mathematical models | Spectra | Behavior | Representations | Statistics | Density | Handling

angular density, asymptotic independence, extremal coefficient, extreme values, max‐stable distribution, non‐central extended skew‐t distribution, non‐stationarity, skew‐normal distribution, skew‐normal process, skew‐t distribution | angular density, asymptotic independence, extremal coefficient, extreme values, max-stable distribution, non-central extended skew-t distribution, non-stationarity, skew-normal distribution, skew-normal process, skew-t distribution | FIELDS | max-stable distribution | skew-t distribution | STATISTICS | skew-normal distribution | REPRESENTATION | STATISTICS & PROBABILITY | NORMAL DISTRIBUTIONS | non-central extended skew-t distribution | non-stationarity | extreme values | angular density | extremal coefficient | VALUES | MAX-STABLE PROCESSES | skew-normal process | asymptotic independence | MULTIVARIATE EXTREMES | Studies | Normal distribution | Statistical analysis | Covariance | Mathematical models | Spectra | Behavior | Representations | Statistics | Density | Handling

Journal Article

Scandinavian Journal of Statistics, ISSN 0303-6898, 9/2006, Volume 33, Issue 3, pp. 561 - 574

The distribution theory literature connected to the multivariate skew-normal distribution has grown rapidly in recent years, and a number of extensions and...

Gaussian distributions | Algebra | Generating function | Mathematical independent variables | Matrices | Random variables | Skewed distribution | Covariance matrices | T distribution | Distribution functions | skew‐elliptical family | stochastic representation | skew‐t distribution | skew‐normal distribution | skew-t distribution | MODELS | skew-elliptical family | skew-normal distribution | T-DISTRIBUTION | STATISTICS & PROBABILITY | Studies | Statistical methods

Gaussian distributions | Algebra | Generating function | Mathematical independent variables | Matrices | Random variables | Skewed distribution | Covariance matrices | T distribution | Distribution functions | skew‐elliptical family | stochastic representation | skew‐t distribution | skew‐normal distribution | skew-t distribution | MODELS | skew-elliptical family | skew-normal distribution | T-DISTRIBUTION | STATISTICS & PROBABILITY | Studies | Statistical methods

Journal Article

IEEE Signal Processing Letters, ISSN 1070-9908, 11/2015, Volume 22, Issue 11, pp. 1898 - 1902

Filtering and smoothing algorithms for linear discrete- time state-space models with skewed and heavy-tailed measurement noise are presented. The algorithms...

Smoothing methods | Computational modeling | Noise | Kalman filter | variational Bayes | Noise measurement | Approximation methods | skew t | robust filtering | t -distribution | RTS smoother | Signal processing algorithms | Approximation algorithms | skewness | t-distribution | DISTRIBUTIONS | MIXTURES | BAYESIAN-INFERENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Teknik och teknologier | Engineering and Technology | Elektroteknik och elektronik | Electrical Engineering, Electronic Engineering, Information Engineering | Kalman filter; robust filtering; RTS smoother; skew t; skewness; t-distribution; variational Bayes

Smoothing methods | Computational modeling | Noise | Kalman filter | variational Bayes | Noise measurement | Approximation methods | skew t | robust filtering | t -distribution | RTS smoother | Signal processing algorithms | Approximation algorithms | skewness | t-distribution | DISTRIBUTIONS | MIXTURES | BAYESIAN-INFERENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Teknik och teknologier | Engineering and Technology | Elektroteknik och elektronik | Electrical Engineering, Electronic Engineering, Information Engineering | Kalman filter; robust filtering; RTS smoother; skew t; skewness; t-distribution; variational Bayes

Journal Article

Journal of Hydrology, ISSN 0022-1694, 2012, Volume 412, pp. 101 - 113

► Highly dimensional flood scenarios are generated for the Upper Mississippi River. ► Two approaches: multivariate skew- distribution and -copula function. ►...

Skew- t distribution | Multivariate processes | Flood scenarios | Flood risk management | Mississippi River | Skew-t distribution | T-DISTRIBUTION | MULTIVARIATE | WATER RESOURCES | SKEW-NORMAL-DISTRIBUTION | DISTRIBUTIONS | ENGINEERING, CIVIL | GEOSCIENCES, MULTIDISCIPLINARY | COPULA | Floods | Hydrology | Gauging stations | Risk | Mathematical models | Rivers | Assessments | Flooding

Skew- t distribution | Multivariate processes | Flood scenarios | Flood risk management | Mississippi River | Skew-t distribution | T-DISTRIBUTION | MULTIVARIATE | WATER RESOURCES | SKEW-NORMAL-DISTRIBUTION | DISTRIBUTIONS | ENGINEERING, CIVIL | GEOSCIENCES, MULTIDISCIPLINARY | COPULA | Floods | Hydrology | Gauging stations | Risk | Mathematical models | Rivers | Assessments | Flooding

Journal Article

Journal of the Royal Statistical Society. Series B (Statistical Methodology), ISSN 1369-7412, 1/2003, Volume 65, Issue 1, pp. 159 - 174

A tractable skew t-distribution on the real line is proposed. This includes as a special case the symmetric t-distribution, and otherwise provides skew...

Maximum likelihood estimation | Degrees of freedom | Inference | Mathematical functions | Data models | Standard error | Skewed distribution | T distribution | Blood flow | Symmetry | Beta distribution | Robustness | Student's t‐distribution | Skewness | Likelihood inference | Student's t-distribution | ROBUST | APPROXIMATIONS | beta distribution | REGRESSION-MODELS | likelihood inference | robustness | STATISTICS & PROBABILITY | skewness | INFERENCE | student's t-distribution

Maximum likelihood estimation | Degrees of freedom | Inference | Mathematical functions | Data models | Standard error | Skewed distribution | T distribution | Blood flow | Symmetry | Beta distribution | Robustness | Student's t‐distribution | Skewness | Likelihood inference | Student's t-distribution | ROBUST | APPROXIMATIONS | beta distribution | REGRESSION-MODELS | likelihood inference | robustness | STATISTICS & PROBABILITY | skewness | INFERENCE | student's t-distribution

Journal Article

Behavior Research Methods, ISSN 1554-351X, 6/2016, Volume 48, Issue 2, pp. 427 - 444

Growth curve models are widely used in social and behavioral sciences. However, typical growth curve models often assume that the errors are normally...

t -distribution | Growth curve models | Bayesian estimation | Psychology | Non-normal data | Exponential power distribution | Cognitive Psychology | SAS PROC MCMC | Skew normal distribution | t-distribution | STUDENTS T DISTRIBUTION | LONGITUDINAL DATA | PSYCHOLOGY, EXPERIMENTAL | CHAIN MONTE-CARLO | STRUCTURAL EQUATION MODELS | PSYCHOLOGY, MATHEMATICAL | DIAGNOSTICS | Computer Simulation | Humans | Bayes Theorem | Child, Preschool | Child Development | Models, Statistical | Longitudinal Studies | Surveys | Computation | Statistical Distributions | Bayesian Statistics | Models | Monte Carlo Methods | Markov Processes | Children

t -distribution | Growth curve models | Bayesian estimation | Psychology | Non-normal data | Exponential power distribution | Cognitive Psychology | SAS PROC MCMC | Skew normal distribution | t-distribution | STUDENTS T DISTRIBUTION | LONGITUDINAL DATA | PSYCHOLOGY, EXPERIMENTAL | CHAIN MONTE-CARLO | STRUCTURAL EQUATION MODELS | PSYCHOLOGY, MATHEMATICAL | DIAGNOSTICS | Computer Simulation | Humans | Bayes Theorem | Child, Preschool | Child Development | Models, Statistical | Longitudinal Studies | Surveys | Computation | Statistical Distributions | Bayesian Statistics | Models | Monte Carlo Methods | Markov Processes | Children

Journal Article

Statistics and Computing, ISSN 0960-3174, 11/2014, Volume 24, Issue 6, pp. 971 - 984

We propose a family of multivariate heavy-tailed distributions that allow variable marginal amounts of tailweight. The originality comes from introducing...

Statistics and Computing/Statistics Programs | Gaussian scale mixture | Covariance matrix decomposition | EM algorithm | Artificial Intelligence (incl. Robotics) | Statistical Theory and Methods | Multivariate generalized t -distribution | Outlier detection | Statistics | Probability and Statistics in Computer Science | Multivariate generalized t-distribution | MIXTURE | STATISTICS & PROBABILITY | T-DISTRIBUTIONS | MULTITUDE | DENSITY | DISCRIMINANT-ANALYSIS | FREEDOM | COMPUTER SCIENCE, THEORY & METHODS | EM algorithm | Algorithms | Gaussian processes

Statistics and Computing/Statistics Programs | Gaussian scale mixture | Covariance matrix decomposition | EM algorithm | Artificial Intelligence (incl. Robotics) | Statistical Theory and Methods | Multivariate generalized t -distribution | Outlier detection | Statistics | Probability and Statistics in Computer Science | Multivariate generalized t-distribution | MIXTURE | STATISTICS & PROBABILITY | T-DISTRIBUTIONS | MULTITUDE | DENSITY | DISCRIMINANT-ANALYSIS | FREEDOM | COMPUTER SCIENCE, THEORY & METHODS | EM algorithm | Algorithms | Gaussian processes

Journal Article

Computational Statistics and Data Analysis, ISSN 0167-9473, 2011, Volume 55, Issue 3, pp. 1196 - 1214

Recently an efficient fixed point algorithm, called maximization by parts (MBP), for finding maximum likelihood estimates has been applied to models based on...

Meta- [formula omitted] distribution | Maximization by parts | Maximum likelihood estimation | Copula | Rolling windows | Inference for margins | Meta-t distribution | STATISTICS & PROBABILITY | Meta t distribution | INFERENCE | DEPENDENT RANDOM-VARIABLES | DENSITY | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | MULTIVARIATE MODELS | STOCK-MARKET | VINES | TIME-SERIES | CONSTRUCTIONS | Copula Inference for margins Maximum likelihood estimation Maximization by parts Meta-t distribution Rolling windows | Algorithms | Maximization | Mathematical analysis | Exact solutions | Data processing | Decomposition | Gaussian | Mathematical models | Statistics

Meta- [formula omitted] distribution | Maximization by parts | Maximum likelihood estimation | Copula | Rolling windows | Inference for margins | Meta-t distribution | STATISTICS & PROBABILITY | Meta t distribution | INFERENCE | DEPENDENT RANDOM-VARIABLES | DENSITY | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | MULTIVARIATE MODELS | STOCK-MARKET | VINES | TIME-SERIES | CONSTRUCTIONS | Copula Inference for margins Maximum likelihood estimation Maximization by parts Meta-t distribution Rolling windows | Algorithms | Maximization | Mathematical analysis | Exact solutions | Data processing | Decomposition | Gaussian | Mathematical models | Statistics

Journal Article

Journal of Mathematical Imaging and Vision, ISSN 0924-9907, 10/2018, Volume 60, Issue 8, pp. 1355 - 1365

A spatially varying Gamma mixture model prior is employed for tomographic image reconstruction, ensuring effective noise elimination and the preservation of...

Mathematical Methods in Physics | Signal,Image and Speech Processing | Spatially varying Gamma mixture models | Edge preservation | Computer Science | Image Processing and Computer Vision | Expectation–maximization (EM) algorithm | Student’s t -distribution | Applications of Mathematics | Iterative image reconstruction | Emission tomography | Student’s t-distribution | COMPUTER SCIENCE, SOFTWARE ENGINEERING | Student's t-distribution | MATHEMATICS, APPLIED | Expectation-maximization (EM) algorithm | MODEL | COMPUTED-TOMOGRAPHY | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Computer science | Markov processes | Algorithms | Analysis

Mathematical Methods in Physics | Signal,Image and Speech Processing | Spatially varying Gamma mixture models | Edge preservation | Computer Science | Image Processing and Computer Vision | Expectation–maximization (EM) algorithm | Student’s t -distribution | Applications of Mathematics | Iterative image reconstruction | Emission tomography | Student’s t-distribution | COMPUTER SCIENCE, SOFTWARE ENGINEERING | Student's t-distribution | MATHEMATICS, APPLIED | Expectation-maximization (EM) algorithm | MODEL | COMPUTED-TOMOGRAPHY | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Computer science | Markov processes | Algorithms | Analysis

Journal Article

Statistics in Medicine, ISSN 0277-6715, 07/2016, Volume 35, Issue 15, pp. 2525 - 2542

Generic drugs have been commercialized in numerous countries. Most of these countries approve the commercialization of a generic drug when there is evidence of...

multivariate skew‐t distribution | Bayesian inference | copula functions | extended generalized gamma distribution | average bioequivalence | Multivariate skew-t distribution | Copula functions | Average bioequivalence | Extended generalized gamma distribution | MEDICINE, RESEARCH & EXPERIMENTAL | TRIALS | MEDICAL INFORMATICS | T-DISTRIBUTION | MULTIVARIATE | POWER | STATISTICS & PROBABILITY | BIOAVAILABILITY | EQUIVALENCE | multivariate skew-t distribution | PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH | MODELS | MATHEMATICAL & COMPUTATIONAL BIOLOGY | SIDED TESTS PROCEDURE | Data Interpretation, Statistical | Humans | Statistical Distributions | Bayes Theorem | Drugs, Generic | Therapeutic Equivalency | Independent regulatory commissions | Usage | Information management | Drug approval | Analysis

multivariate skew‐t distribution | Bayesian inference | copula functions | extended generalized gamma distribution | average bioequivalence | Multivariate skew-t distribution | Copula functions | Average bioequivalence | Extended generalized gamma distribution | MEDICINE, RESEARCH & EXPERIMENTAL | TRIALS | MEDICAL INFORMATICS | T-DISTRIBUTION | MULTIVARIATE | POWER | STATISTICS & PROBABILITY | BIOAVAILABILITY | EQUIVALENCE | multivariate skew-t distribution | PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH | MODELS | MATHEMATICAL & COMPUTATIONAL BIOLOGY | SIDED TESTS PROCEDURE | Data Interpretation, Statistical | Humans | Statistical Distributions | Bayes Theorem | Drugs, Generic | Therapeutic Equivalency | Independent regulatory commissions | Usage | Information management | Drug approval | Analysis

Journal Article

Mediterranean Journal of Mathematics, ISSN 1660-5446, 8/2018, Volume 15, Issue 4, pp. 1 - 13

Although there are some results related to classical bivariate Student-t distribution, studying the exact distribution of its extremes is not so easy. However,...

moments | Marshall–Olkin-type bivariate Student- t distribution | Mathematics, general | 60G70 | Mathematics | 62G32 | 62E15 | Extreme values | Marshall–Olkin-type bivariate Student-t distribution | MATHEMATICS | MATHEMATICS, APPLIED | Marshall-Olkin-type bivariate Student-t distribution | EXPONENTIAL-DISTRIBUTION | BIVARIATE-T

moments | Marshall–Olkin-type bivariate Student- t distribution | Mathematics, general | 60G70 | Mathematics | 62G32 | 62E15 | Extreme values | Marshall–Olkin-type bivariate Student-t distribution | MATHEMATICS | MATHEMATICS, APPLIED | Marshall-Olkin-type bivariate Student-t distribution | EXPONENTIAL-DISTRIBUTION | BIVARIATE-T

Journal Article

Journal of Visual Communication and Image Representation, ISSN 1047-3203, 10/2016, Volume 40, pp. 345 - 356

Because of the Student- distribution owning heavier tailed than the Gaussian distribution, under a Bayesian framework, a spatially variant finite mixture model...

Gaussian distribution | Spatially variant finite mixture model | Expectation-maximization algorithm | Grayscale image segmentation | Student’s t-distribution | Bayesian framework | Student's t-distribution | COMPUTER SCIENCE, SOFTWARE ENGINEERING | DIGITAL BRAIN PHANTOM | ALGORITHM | COMPUTER SCIENCE, INFORMATION SYSTEMS | T-DISTRIBUTIONS | Image processing | Models | Analysis

Gaussian distribution | Spatially variant finite mixture model | Expectation-maximization algorithm | Grayscale image segmentation | Student’s t-distribution | Bayesian framework | Student's t-distribution | COMPUTER SCIENCE, SOFTWARE ENGINEERING | DIGITAL BRAIN PHANTOM | ALGORITHM | COMPUTER SCIENCE, INFORMATION SYSTEMS | T-DISTRIBUTIONS | Image processing | Models | Analysis

Journal Article