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Journal articles on the topic 'Skew-t'

Author: Grafiati

Published: 4 June 2021

Last updated: 6 February 2022

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1

Nugroho, Didit Budi, Agus Priyono, and Bambang Susanto. "SKEW NORMAL AND SKEW STUDENT-T DISTRIBUTIONS ON GARCH(1,1) MODEL." MEDIA STATISTIKA 14, no. 1 (2021): 21–32. http://dx.doi.org/10.14710/medstat.14.1.21-32.

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The Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) type models have become important tools in financial application since their ability to estimate the volatility of financial time series data. In the empirical financial literature, the presence of skewness and heavy-tails have impacts on how well the GARCH-type models able to capture the financial market volatility sufficiently. This study estimates the volatility of financial asset returns based on the GARCH(1,1) model assuming Skew Normal and Skew Student-t distributions for the returns errors. The models are applied to d

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2

GUPTA, A. K. "MULTIVARIATE SKEW t -DISTRIBUTION." Statistics: A Journal of Theoretical and Applied Statistics 37, no. 4 (2003): 1. http://dx.doi.org/10.1080/0233188031000123771.

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3

Lee, Sharon X., and Geoffrey J. McLachlan. "On mixtures of skew normal and skew $$t$$ -distributions." Advances in Data Analysis and Classification 7, no. 3 (2013): 241–66. http://dx.doi.org/10.1007/s11634-013-0132-8.

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4

Chamroukhi, F. "Skew t mixture of experts." Neurocomputing 266 (November 2017): 390–408. http://dx.doi.org/10.1016/j.neucom.2017.05.044.

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5

Acitas, Sukru, Birdal Senoglu, and Olcay Arslan. "Alpha-Skew Generalized t Distribution." Revista Colombiana de Estadística 38, no. 2 (2015): 371–84. http://dx.doi.org/10.15446/rce.v38n2.51665.

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<p>The alpha-skew normal (ASN) distribution has been proposed recently in the literature by using standard normal distribution and a skewing approach. Although ASN distribution is able to model both skew and bimodal data, it is shortcoming when data has thinner or thicker tails than normal. Therefore, we propose an alpha-skew generalized t (ASGT) by using the generalized t (GT) distribution and a new skewing procedure. From this point of view, ASGT can be seen as an alternative skew version of GT distribution. However, ASGT differs from the previous skew versions of GT distribution since

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6

Dey, Kumar, Chandra Paul та Bijan Davvaz. "On gamma-rings with (σ, t )-skew-commuting and (σ, t )-skew-centralizing mappings". Kragujevac Journal of Mathematics 42, № 1 (2018): 41–50. http://dx.doi.org/10.5937/kgjmath1801041d.

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7

Kollo, Tõnu, Meelis Käärik, and Anne Selart. "Multivariate Skew t-Distribution: Asymptotics for Parameter Estimators and Extension to Skew t-Copula." Symmetry 13, no. 6 (2021): 1059. http://dx.doi.org/10.3390/sym13061059.

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Symmetric elliptical distributions have been intensively used in data modeling and robustness studies. The area of applications was considerably widened after transforming elliptical distributions into the skew elliptical ones that preserve several good properties of the corresponding symmetric distributions and increase possibilities of data modeling. We consider three-parameter p-variate skew t-distribution where p-vector μ is the location parameter, Σ:p×p is the positive definite scale parameter, p-vector α is the skewness or shape parameter, and the number of degrees of freedom ν is fixed.

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8

EROĞLU İNAN, Gültaç. "Change-constrained stochastic programming problem with normal, t and skew normal, skew t distributions." Communications Faculty Of Science University of Ankara Series A1Mathematics and Statistics 70, no. 1 (2021): 180–93. http://dx.doi.org/10.31801/cfsuasmas.685733.

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9

Punathumparambath, Bindu. "The multivariate skew-slash t and skew-slash Cauchy distributions." Model Assisted Statistics and Applications 7, no. 1 (2012): 33–40. http://dx.doi.org/10.3233/mas-2011-0199.

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10

Son, Sookyoung, Hyunjung Lee, Yoona Jang, Junyeong Yang, and Sehee Hong. "A Comparison of Different Nonnormal Distributions in Growth Mixture Models." Educational and Psychological Measurement 79, no. 3 (2019): 577–97. http://dx.doi.org/10.1177/0013164418823865.

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The purpose of the present study is to compare nonnormal distributions (i.e., t, skew-normal, skew- t with equal skew and skew- t with unequal skew) in growth mixture models (GMMs) based on diverse conditions of a number of time points, sample sizes, and skewness for intercepts. To carry out this research, two simulation studies were conducted with two different models: an unconditional GMM and a GMM with a continuous distal outcome variable. For the simulation, data were generated under the conditions of a different number of time points (4, 8), sample size (300, 800, 1,500), and skewness for

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11

Azzalini, Adelchi, and Reinaldo B. Arellano-Valle. "Maximum penalized likelihood estimation for skew-normal and skew-t distributions." Journal of Statistical Planning and Inference 143, no. 2 (2013): 419–33. http://dx.doi.org/10.1016/j.jspi.2012.06.022.

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12

Maghami, Mohammad Mahdi, Mohammad Bahrami, and Farkhondeh Alsadat Sajadi. "On bias reduction estimators of skew-normal and skew-t distributions." Journal of Applied Statistics 47, no. 16 (2020): 3030–52. http://dx.doi.org/10.1080/02664763.2019.1710114.

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13

Nadarajah, Saralees, and Arjun Gupta. "Skew t distribution and its moments." Progress in Natural Science 16, no. 10 (2006): 1033–37. http://dx.doi.org/10.1080/10020070612330106.

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14

Kollo, Tõnu, Gaida Pettere, and Marju Valge. "Tail dependence of skew t-copulas." Communications in Statistics - Simulation and Computation 46, no. 2 (2016): 1024–34. http://dx.doi.org/10.1080/03610918.2014.988979.

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15

Murray, Paula M., Ryan P. Browne, and Paul D. McNicholas. "Mixtures of skew-t factor analyzers." Computational Statistics & Data Analysis 77 (September 2014): 326–35. http://dx.doi.org/10.1016/j.csda.2014.03.012.

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16

Gallaugher, Michael P. B., and Paul D. McNicholas. "A matrix variate skew-t distribution." Stat 6, no. 1 (2017): 160–70. http://dx.doi.org/10.1002/sta4.143.

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17

Mazurek, Ryszard. "Rota–Baxter operators on skew generalized power series rings." Journal of Algebra and Its Applications 13, no. 07 (2014): 1450048. http://dx.doi.org/10.1142/s0219498814500480.

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Let R be a ring, S a strictly ordered monoid, and ω : S → End (R) a monoid homomorphism. The skew generalized power series ring R[[S, ω]] is a common generalization of (skew) polynomial rings, (skew) Laurent polynomial rings, (skew) power series rings, (skew) Laurent series rings, (skew) monoid rings, (skew) Mal'cev–Neumann series rings, and generalized power series rings. We characterize those subsets T of S for which the cut-off operator with respect to T is a Rota–Baxter operator on the ring R[[S, ω]]. The obtained results provide a large class of noncommutative Rota–Baxter algebras.

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18

Lee, Sharon X., and Geoffrey J. McLachlan. "Finite mixtures of canonical fundamental skew $$t$$ t -distributions." Statistics and Computing 26, no. 3 (2015): 573–89. http://dx.doi.org/10.1007/s11222-015-9545-x.

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19

Chō, Muneo, Eungil Ko, and Ji Lee. "Skew m-complex symmetric operators." Filomat 33, no. 10 (2019): 2975–83. http://dx.doi.org/10.2298/fil1910975c.

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In this paper we study skew m-complex symmetric operators. In particular, we show that if T ? L(H) is a skew m-complex symmetric operator with a conjugation C, then eitT , e-itT , and e-itT* are (m,C)-isometric for every t ? R. Moreover, we examine some conditions for skew m-complex symmetric operators to be skew (m-1)-complex symmetric.

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20

Roy, Satya Sapath, Jamshaid Sawab, Tianmin Zhou, Y. L. Mo, and Thomas T. C. Hsu. "Performance of Skew Reinforcing in Inverted-T Bridge Caps." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 41 (2018): 65–74. http://dx.doi.org/10.1177/0361198118756892.

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Inverted-T bridge caps (ITBCs) have been widely used in most bridges in Texas in recent years. In some typical cases, the bridge caps are skew when two roads are not aligned in a perpendicular manner. The traditional method of flaring the transverse reinforcement out in skew ITBCs introduces significant complexity in design and during construction. An alternative is to provide skew reinforcing which will substantially reduce the design complexities and construction period. In this paper, three ITBC specimens were subjected to shear action to evaluate and compare the performance of ITBCs with t

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21

Masjkur, Mohammad, and Henk Folmer. "Bayesian Estimation of Random Parameter Models of Responses with Normal and Skew-t Distibutions Evidence from Monte Carlo Simulation." Journal of the Indonesian Mathematical Society 24, no. 1 (2018): 27–50. http://dx.doi.org/10.22342/jims.24.1.516.27-50.

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Random parameter models have been found to outperform xed pa-rameter models to estimate dose-response relationships with independent errors. Amajor restriction, however, is that the responses are assumed to be normally andsymmetrically distributed. The purpose of this paper is to analyze Bayesian infer-ence of random parameter response models in the case of independent responseswith normal and skewed, heavy-tailed distributions by way of Monte Carlo simu-lation. Three types of Bayesian estimators are considered: one applying a normal,symmetrical prior distribution, a second applying a Skew-nor

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22

Padoan, Simone A. "Multivariate extreme models based on underlying skew-t and skew-normal distributions." Journal of Multivariate Analysis 102, no. 5 (2011): 977–91. http://dx.doi.org/10.1016/j.jmva.2011.01.014.

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23

Frühwirth-Schnatter, Sylvia, and Saumyadipta Pyne. "Bayesian inference for finite mixtures of univariate and multivariate skew-normal and skew-t distributions." Biostatistics 11, no. 2 (2010): 317–36. http://dx.doi.org/10.1093/biostatistics/kxp062.

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Abstract Skew-normal and skew-t distributions have proved to be useful for capturing skewness and kurtosis in data directly without transformation. Recently, finite mixtures of such distributions have been considered as a more general tool for handling heterogeneous data involving asymmetric behaviors across subpopulations. We consider such mixture models for both univariate as well as multivariate data. This allows robust modeling of high-dimensional multimodal and asymmetric data generated by popular biotechnological platforms such as flow cytometry. We develop Bayesian inference based on da

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24

Ahsanullah, Mohammad, and Valery B. Nevzorov. "Some Characterizations of Skew t-distribution of Three Degrees of Freedom." Calcutta Statistical Association Bulletin 71, no. 1 (2019): 40–48. http://dx.doi.org/10.1177/0008068319839818.

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25

Abid, Salah, Uday Quaez, and Javier Contreras-Reyes. "An Information-Theoretic Approach for Multivariate Skew-t Distributions and Applications." Mathematics 9, no. 2 (2021): 146. http://dx.doi.org/10.3390/math9020146.

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Shannon and Rényi entropies are two important measures of uncertainty for data analysis. These entropies have been studied for multivariate Student-t and skew-normal distributions. In this paper, we extend the Rényi entropy to multivariate skew-t and finite mixture of multivariate skew-t (FMST) distributions. This class of flexible distributions allows handling asymmetry and tail weight behavior simultaneously. We find upper and lower bounds of Rényi entropy for these families. Numerical simulations illustrate the results for several scenarios: symmetry/asymmetry and light/heavy-tails. Finally

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26

Abid, Salah, Uday Quaez, and Javier Contreras-Reyes. "An Information-Theoretic Approach for Multivariate Skew-t Distributions and Applications." Mathematics 9, no. 2 (2021): 146. http://dx.doi.org/10.3390/math9020146.

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Shannon and Rényi entropies are two important measures of uncertainty for data analysis. These entropies have been studied for multivariate Student-t and skew-normal distributions. In this paper, we extend the Rényi entropy to multivariate skew-t and finite mixture of multivariate skew-t (FMST) distributions. This class of flexible distributions allows handling asymmetry and tail weight behavior simultaneously. We find upper and lower bounds of Rényi entropy for these families. Numerical simulations illustrate the results for several scenarios: symmetry/asymmetry and light/heavy-tails. Finally

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27

Yousefi, Ramesh, and Mansour Dana. "On linear operators for which TTD is normal." Filomat 33, no. 9 (2019): 2695–704. http://dx.doi.org/10.2298/fil1909695y.

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A Drazin invertible operator T ? B(H) is called skew D-quasi-normal operator if T* and TTD commute or equivalently TTD is normal. In this paper, firstly we give a list of conditions on an operator T; each of which is equivalent to T being skew D-quasi-normal. Furthermore, we obtain the matrix representation of these operators. We also develop some basic properties of such operators. Secondly we extend the Kaplansky theorem and the Fuglede-Putnam commutativity theorem for normal operators to skew D-quasi-normal matrices.

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28

Adubisi, O. D., A. Abdulkadir, and H. Chiroma. "A Two Parameter Odd Exponentiated Skew-T Distribution With J-Shaped Hazard Rate Function." Journal of Statistical Modelling and Analytics 3, no. 1 (2021): 26–46. http://dx.doi.org/10.22452/josma.vol3no1.3.

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A new generalization of the skew-t distribution was proposed. The two-parameter lifetime model called the odd exponentiated skew-t distribution has the ability of fitting skewed, long and heavy tailed datasets. It is considered to be more flexible than the skew-t distribution as it contains it as a special case. Some basic properties of the distribution such as the order statistics, entropy, asymptotic behaviour, moment, incomplete moment, characteristic function and quantile function were derived. The odd exponentiated skew-t distribution parameter estimates were derived using the maximum lik

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29

Tovar-Falón, Roger, Heleno Bolfarine, and Guillermo Martínez-Flórez. "The Asymmetric Alpha-Power Skew-t Distribution." Symmetry 12, no. 1 (2020): 82. http://dx.doi.org/10.3390/sym12010082.

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In this paper, we propose a new asymmetric and heavy-tail model that generalizes both the skew-t and power-t models. Properties of the model are studied in detail. The score functions and the elements of the observed information matrix are given. The process to estimate the parameters in model is discussed by using the maximum likelihood approach. Also, the observed information matrix is shown to be non-singular at the whole parametric space. Two applications to real data sets are reported to demonstrate the usefulness of this new model.

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30

Peng, Zuoxiang, Chunqiao Li, and Saralees Nadarajah. "Extremal properties of the skew-t distribution." Statistics & Probability Letters 112 (May 2016): 10–19. http://dx.doi.org/10.1016/j.spl.2016.01.017.

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31

Aas, K. "The Generalized Hyperbolic Skew Student's t-Distribution." Journal of Financial Econometrics 4, no. 2 (2006): 275–309. http://dx.doi.org/10.1093/jjfinec/nbj006.

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32

Huang, Wen-Jang, Nan-Cheng Su, and Hui-Yi Teng. "On some study of skew-t distributions." Communications in Statistics - Theory and Methods 48, no. 19 (2019): 4712–29. http://dx.doi.org/10.1080/03610926.2012.700369.

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33

Maestrini, Luca, and Matt P. Wand. "Variational message passing for skew t regression." Stat 7, no. 1 (2018): e196. http://dx.doi.org/10.1002/sta4.196.

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34

Otiniano, C. E. G., P. N. Rathie, and L. C. S. M. Ozelim. "On the identifiability of finite mixture of Skew-Normal and Skew-t distributions." Statistics & Probability Letters 106 (November 2015): 103–8. http://dx.doi.org/10.1016/j.spl.2015.07.015.

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35

Lee, Sharon X., Kaleb L. Leemaqz, and Geoffrey J. McLachlan. "A Block EM Algorithm for Multivariate Skew Normal and Skew $t$ -Mixture Models." IEEE Transactions on Neural Networks and Learning Systems 29, no. 11 (2018): 5581–91. http://dx.doi.org/10.1109/tnnls.2018.2805317.

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36

Marchenko, Yulia V., and Marc G. Genton. "A Suite of Commands for Fitting the Skew-normal and Skew-t models." Stata Journal: Promoting communications on statistics and Stata 10, no. 4 (2011): 507–39. http://dx.doi.org/10.1177/1536867x1001000401.

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37

Marchenko, Yulia V., and Marc G. Genton. "A Suite of Commands for Fitting the Skew-normal and Skew-t models." Stata Journal: Promoting communications on statistics and Stata 10, no. 4 (2010): 507–39. http://dx.doi.org/10.1177/1536867x1101000401.

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38

Greco, Luca. "Minimum Hellinger distance based inference for scalar skew-normal and skew-t distributions." TEST 20, no. 1 (2010): 120–37. http://dx.doi.org/10.1007/s11749-010-0191-5.

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39

Tang, Yongqiang. "A monotone data augmentation algorithm for longitudinal data analysis via multivariate skew-t, skew-normal or t distributions." Statistical Methods in Medical Research 29, no. 6 (2019): 1542–62. http://dx.doi.org/10.1177/0962280219865579.

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The mixed effects model for repeated measures has been widely used for the analysis of longitudinal clinical data collected at a number of fixed time points. We propose a robust extension of the mixed effects model for repeated measures for skewed and heavy-tailed data on basis of the multivariate skew-t distribution, and it includes the multivariate normal, t, and skew-normal distributions as special cases. An efficient Markov chain Monte Carlo algorithm is developed using the monotone data augmentation and parameter expansion techniques. We employ the algorithm to perform controlled pattern

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40

Adcock, Christopher. "Copulaesque Versions of the Skew-Normal and Skew-Student Distributions." Symmetry 13, no. 5 (2021): 815. http://dx.doi.org/10.3390/sym13050815.

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A recent paper presents an extension of the skew-normal distribution which is a copula. Under this model, the standardized marginal distributions are standard normal. The copula itself depends on the familiar skewing construction based on the normal distribution function. This paper is concerned with two topics. First, the paper presents a number of extensions of the skew-normal copula. Notably these include a case in which the standardized marginal distributions are Student’s t, with different degrees of freedom allowed for each margin. In this case the skewing function need not be the distri

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41

AICHHOLZER, OSWIN, FRANZ AURENHAMMER, DANNY Z. CHEN, D. T. LEE, and EVANTHIA PAPADOPOULOU. "SKEW VORONOI DIAGRAMS." International Journal of Computational Geometry & Applications 09, no. 03 (1999): 235–47. http://dx.doi.org/10.1142/s0218195999000169.

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On a tilted plane T in three-space, skew distances are defined as the Euclidean distance plus a multiple of the signed difference in height. Skew distances may model realistic environments more closely than the Euclidean distance. Voronoi diagrams and related problems under this kind of distances are investigated. A relationship to convex distance functions and to Euclidean Voronoi diagrams for planar circles is shown, and is exploited for a geometric analysisis and a plane-sweep construction of Voronoi diagrams on T. An output-sensitive algorithm running in time O(n log h) is developed, where

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42

Chen, Xuedong, Qianying Zeng, and Qiankun Song. "Likelihood Inference of Nonlinear Models Based on a Class of Flexible Skewed Distributions." Abstract and Applied Analysis 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/542985.

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This paper deals with the issue of the likelihood inference for nonlinear models with a flexible skew-t-normal (FSTN) distribution, which is proposed within a general framework of flexible skew-symmetric (FSS) distributions by combining with skew-t-normal (STN) distribution. In comparison with the common skewed distributions such as skew normal (SN), and skew-t (ST) as well as scale mixtures of skew normal (SMSN), the FSTN distribution can accommodate more flexibility and robustness in the presence of skewed, heavy-tailed, especially multimodal outcomes. However, for this distribution, a usual

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43

Sartori, Nicola. "Bias prevention of maximum likelihood estimates for scalar skew normal and skew t distributions." Journal of Statistical Planning and Inference 136, no. 12 (2006): 4259–75. http://dx.doi.org/10.1016/j.jspi.2005.08.043.

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44

Wang, Sheng, Dale L. Zimmerman, and Patrick Breheny. "Sparsity-regularized skewness estimation for the multivariate skew normal and multivariate skew t distributions." Journal of Multivariate Analysis 179 (September 2020): 104639. http://dx.doi.org/10.1016/j.jmva.2020.104639.

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45

Abdikalykov, A. K., Kh D. Ikramov, and V. N. Chugunov. "On eigenvalues of (T + H)-circulants and (T + H)-skew-circulants." Numerical Analysis and Applications 7, no. 2 (2014): 91–103. http://dx.doi.org/10.1134/s1995423914020037.

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46

Ghaderinezhad, Fatemeh, Christophe Ley, and Nicola Loperfido. "Bayesian Inference for Skew-Symmetric Distributions." Symmetry 12, no. 4 (2020): 491. http://dx.doi.org/10.3390/sym12040491.

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Skew-symmetric distributions are a popular family of flexible distributions that conveniently model non-normal features such as skewness, kurtosis and multimodality. Unfortunately, their frequentist inference poses several difficulties, which may be adequately addressed by means of a Bayesian approach. This paper reviews the main prior distributions proposed for the parameters of skew-symmetric distributions, with special emphasis on the skew-normal and the skew-t distributions which are the most prominent skew-symmetric models. The paper focuses on the univariate case in the absence of covari

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47

Basalamah, Doaa, Wei Ning, and Arjun Gupta. "The beta skew t distribution and its properties." Journal of Statistical Theory and Practice 12, no. 4 (2018): 837–60. http://dx.doi.org/10.1080/15598608.2018.1481468.

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48

Tagle, Felipe, Stefano Castruccio, and Marc G. Genton. "A hierarchical bi-resolution spatial skew-t model." Spatial Statistics 35 (March 2020): 100398. http://dx.doi.org/10.1016/j.spasta.2019.100398.

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49

Bright, Amanda, Gregory Clark, Charles Dunn, et al. "Tiling annular regions with skew and T-tetrominoes." Involve, a Journal of Mathematics 10, no. 3 (2017): 505–21. http://dx.doi.org/10.2140/involve.2017.10.505.

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50

Lin, Jin-Guan, Feng-Chang Xie, and Bo-Cheng Wei. "Statistical Diagnostics for Skew-t-Normal Nonlinear Models." Communications in Statistics - Simulation and Computation 38, no. 10 (2009): 2096–110. http://dx.doi.org/10.1080/03610910903249502.

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