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Measures of kurtosis: inadmissible for asymmetric distributions? Metrika (IF 0.7) Pub Date : 2024-03-17 Andreas Eberl, Bernhard Klar
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Staged trees and asymmetry-labeled DAGs Metrika (IF 0.7) Pub Date : 2024-03-07 Gherardo Varando, Federico Carli, Manuele Leonelli
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Right-censored nonparametric regression with measurement error Metrika (IF 0.7) Pub Date : 2024-03-05 Dursun Aydın, Ersin Yılmaz, Nur Chamidah, Budi Lestari, I. Nyoman Budiantara
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Bootstrap for inference after model selection and model averaging for likelihood models Metrika (IF 0.7) Pub Date : 2024-03-05 Andrea C. Garcia-Angulo, Gerda Claeskens
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On some properties of one nonparametric estimate of poisson regression function Metrika (IF 0.7) Pub Date : 2024-03-01 P. Babilua, E. Nadaraya
The paper considers the nonparametric Poisson regression problem with a regular equidistant design on the unit interval. The nonparametric estimation of the Poisson regression function is studied. The uniform consistency conditions are established and the limit theorems are proved for continuous functionals on \(C[a,1-a]\), \(0
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A multivariate Jacobi polynomials regression estimator associated with an ANOVA decomposition model Metrika (IF 0.7) Pub Date : 2024-02-26
Abstract In this work, we construct a stable and fairly fast estimator for solving multidimensional non-parametric regression problems. The proposed estimator is based on the use of a novel and special system of multivariate Jacobi polynomials that generate a basis for a reduced size of \(d-\) variate finite dimensional polynomials space. An ANOVA decomposition trick has been used for building this
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Minimum $$\theta $$ -aberration criterion for designs with qualitative and quantitative factors Metrika (IF 0.7) Pub Date : 2024-02-23 Liangwei Qi, Yongdao Zhou
The minimum aberration criterion is popular for selecting good designs with qualitative factors under an ANOVA model, and the minimum \(\beta \)-aberration criterion is more suitable for selecting designs with quantitative factors under a polynomial model. However, numerous computer experiments involve both qualitative and quantitative factors, while there is a lack of a reasonable criterion to assess
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Robust estimation and diagnostic of generalized linear model for insurance losses: a weighted likelihood approach Metrika (IF 0.7) Pub Date : 2024-02-23 Tsz Chai Fung
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Bayesian composite $$L^p$$ -quantile regression Metrika (IF 0.7) Pub Date : 2024-02-21
Abstract \(L^p\) -quantiles are a class of generalized quantiles defined as minimizers of an asymmetric power function. They include both quantiles, \(p=1\) , and expectiles, \(p=2\) , as special cases. This paper studies composite \(L^p\) -quantile regression, simultaneously extending single \(L^p\) -quantile regression and composite quantile regression. A Bayesian approach is considered, where a
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Robust beta regression through the logit transformation Metrika (IF 0.7) Pub Date : 2024-02-18 Yuri S. Maluf, Silvia L. P. Ferrari, Francisco F. Queiroz
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On Bayesian predictive density estimation for skew-normal distributions Metrika (IF 0.7) Pub Date : 2024-02-17 Othmane Kortbi
This paper is concerned with prediction for skew-normal models, and more specifically the Bayes estimation of a predictive density for \(Y \left. \right| \mu \sim {\mathcal {S}} {\mathcal {N}}_p (\mu , v_y I_p, \lambda )\) under Kullback–Leibler loss, based on \(X \left. \right| \mu \sim {\mathcal {S}} {\mathcal {N}}_p (\mu , v_x I_p, \lambda )\) with known dependence and skewness parameters. We obtain
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Pointwise density estimation on metric spaces and applications in seismology Metrika (IF 0.7) Pub Date : 2024-02-13 G. Cleanthous, Athanasios G. Georgiadis, P. A. White
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Stochastic comparisons, differential entropy and varentropy for distributions induced by probability density functions Metrika (IF 0.7) Pub Date : 2024-02-09
Abstract Stimulated by the need of describing useful notions related to information measures, we introduce the ‘pdf-related distributions’. These are defined in terms of transformation of absolutely continuous random variables through their own probability density functions. We investigate their main characteristics, with reference to the general form of the distribution, the quantiles, and some related
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On Berry–Esséen bound of frequency polygon estimation under $$\rho $$ -mixing samples Metrika (IF 0.7) Pub Date : 2024-02-06 Yi Wu, Xuejun Wang
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Measure of deviancy from marginal mean equality based on cumulative marginal probabilities in square contingency tables Metrika (IF 0.7) Pub Date : 2024-02-05 Shuji Ando
This study proposes a measure that can concurrently evaluate the degree and direction of deviancy from the marginal mean equality (ME) model in square contingency tables with ordered categories. The proposed measure is constructed as the function of the row and column cumulative marginal probabilities. When the ME model does not fit data, we are interested in measuring the degree of deviancy from the
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Nonparametric estimation of $${\mathbb {P}}(X Metrika (IF 0.7) Pub Date : 2024-01-08 Cao Xuan Phuong, Le Thi Hong Thuy
Let X, Y be continuous random variables with unknown distributions. The aim of this paper is to study the problem of estimating the probability \(\theta := {\mathbb {P}}(X
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Penalized Lq-likelihood estimator and its influence function in generalized linear models Metrika (IF 0.7) Pub Date : 2024-01-07
Abstract Consider the following generalized linear model (GLM) $$\begin{aligned} y_i=h(x_i^T\beta )+e_i,\quad i=1,2,\ldots ,n, \end{aligned}$$ where h(.) is a continuous differentiable function, \(\{e_i\}\) are independent identically distributed (i.i.d.) random variables with zero mean and known variance \(\sigma ^2\) . Based on the penalized Lq-likelihood method of linear regression models, we apply
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The local linear functional kNN estimator of the conditional expectile: uniform consistency in number of neighbors Metrika (IF 0.7) Pub Date : 2024-01-06 Ibrahim M. Almanjahie, Salim Bouzebda, Zoulikha Kaid, Ali Laksaci
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On the asymptotic behaviour of the joint distribution of the maxima and minima of observations, when the sample size is a random variable Metrika (IF 0.7) Pub Date : 2024-01-05 R. Vasudeva
In this paper, we obtain the asymptotic form of the joint distribution of maxima and minima of independent observations, when the sample size is a random variable. We also discuss the asymptotic distribution of the Range.
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Bayesian minimum aberration mixed-level split-plot designs Metrika (IF 0.7) Pub Date : 2024-01-03 Hui Li, Min-Qian Liu, Jinyu Yang
Many industrial experiments involve factors with levels more difficult to change or control than others, which leads to the development of two-level fractional factorial split-plot (FFSP) designs. Recently, mixed-level FFSP designs were proposed due to the requirement of different-level factors. In this paper, we generalize the Bayesian optimal criterion for mixed two- and four-level FFSP designs,
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Mixing convergence of LSE for supercritical AR(2) processes with Gaussian innovations using random scaling Metrika (IF 0.7) Pub Date : 2023-12-27 Mátyás Barczy, Fanni Nedényi, Gyula Pap
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An association measure for spatio-temporal time series Metrika (IF 0.7) Pub Date : 2023-12-23 Divya Kappara, Arup Bose, Madhuchhanda Bhattacharjee
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A tail index estimation for long memory processes Metrika (IF 0.7) Pub Date : 2023-12-20 Xiao Wang, Lihong Wang
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Correcting spot power variation estimator via Edgeworth expansion Metrika (IF 0.7) Pub Date : 2023-12-18 Lidan He, Qiang Liu, Zhi Liu, Andrea Bucci
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A proper selection among multiple Buckley–James estimates Metrika (IF 0.7) Pub Date : 2023-12-14 Qiqing Yu
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Modelling and diagnostic tests for Poisson and negative-binomial count time series Metrika (IF 0.7) Pub Date : 2023-12-13 Boris Aleksandrov, Christian H. Weiß, Simon Nik, Maxime Faymonville, Carsten Jentsch
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Jackknife model averaging for mixed-data kernel-weighted spline quantile regressions Metrika (IF 0.7) Pub Date : 2023-11-28 Xianwen Sun, Lixin Zhang
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Cumulative information generating function and generalized Gini functions Metrika (IF 0.7) Pub Date : 2023-11-27 Marco Capaldo, Antonio Di Crescenzo, Alessandra Meoli
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Stochastic comparisons of two finite mixtures of general family of distributions Metrika (IF 0.7) Pub Date : 2023-11-20 Raju Bhakta, Priyanka Majumder, Suchandan Kayal, Narayanaswamy Balakrishnan
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Bayesian multivariate nonlinear mixed models for censored longitudinal trajectories with non-monotone missing values Metrika (IF 0.7) Pub Date : 2023-10-26 Wan-Lun Wang, Luis M. Castro, Tsung-I Lin
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On the asymptotic behaviour of the joint distribution of the maxima and minima of observations, when the sample size is a random variable Metrika (IF 0.7) Pub Date : 2023-10-17 R. Vasudeva
In this paper, we obtain the asymptotic form of the joint distribution of maxima and minima of independent observations, when the sample size is a random variable. We also discuss the asymptotic distribution of the range.
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The ridge prediction error sum of squares statistic in linear mixed models Metrika (IF 0.7) Pub Date : 2023-10-05 Özge Kuran, M. Revan Özkale
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Large deviations for randomly weighted least squares estimator in a nonlinear regression model Metrika (IF 0.7) Pub Date : 2023-10-04 Yi Wu, Wei Yu, Xuejun Wang
In this work, we introduce the random weighting method to the nonlinear regression model and study the asymptotic properties for the randomly weighted least squares estimator with dependent errors. The results reveal that this new estimator is consistent. Moreover, some simulations are also carried out to show the performance of the proposed estimator.
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Second-order (s.o.) multi-stage fixed-width confidence interval (FWCI) estimation strategies for comparing location parameters from two negative exponential (NE) populations: illustrations with cancer data Metrika (IF 0.7) Pub Date : 2023-10-01 Nitis Mukhopadhyay, Anhar Aloufi
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An inverse Laplace transform oracle estimator for the normal means problem Metrika (IF 0.7) Pub Date : 2023-09-16 Adebowale J. Sijuwade, Swarnita Chakraborty, Nairanjana Dasgupta
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On regression and classification with possibly missing response variables in the data Metrika (IF 0.7) Pub Date : 2023-09-10 Majid Mojirsheibani, William Pouliot, Andre Shakhbandaryan
This paper considers the problem of kernel regression and classification with possibly unobservable response variables in the data, where the mechanism that causes the absence of information can depend on both predictors and the response variables. Our proposed approach involves two steps: First we construct a family of models (possibly infinite dimensional) indexed by the unknown parameter of the
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Additive hazards quantile model Metrika (IF 0.7) Pub Date : 2023-09-11 N. Unnikrishnan Nair, S. M. Sunoj, Namitha Suresh
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The distribution of the sample correlation coefficient under variance-truncated normality Metrika (IF 0.7) Pub Date : 2023-08-25 Haruhiko Ogasawara
The non-null distribution of the sample correlation coefficient under bivariate normality is derived when each of the associated two sample variances is subject to stripe truncation including usual single and double truncation as special cases. The probability density function is obtained using series expressions as in the untruncated case with new definitions of weighted hypergeometric functions.
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A generalisation of the aggregate association index (AAI): incorporating a linear transformation of the cells of a 2 × 2 table Metrika (IF 0.7) Pub Date : 2023-08-16 Eric J. Beh, Duy Tran, Irene L. Hudson
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Bivariate distributions with equi-dispersed normal conditionals and related models Metrika (IF 0.7) Pub Date : 2023-08-07 Barry C. Arnold, B. G. Manjunath
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Refining analytic approximation based estimation of mixed multinomial probit models by parameter selection Metrika (IF 0.7) Pub Date : 2023-07-28 Daniel Rodenburger
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Ordering results for the smallest (largest) and the second smallest (second largest) order statistics of dependent and heterogeneous random variables Metrika (IF 0.7) Pub Date : 2023-07-15 Omid Shojaee, Seyed Morteza Mohammadi, Reza Momeni
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Robust distributed multicategory angle-based classification for massive data Metrika (IF 0.7) Pub Date : 2023-06-28 Gaoming Sun, Xiaozhou Wang, Yibo Yan, Riquan Zhang
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Optimal subsampling for modal regression in massive data Metrika (IF 0.7) Pub Date : 2023-06-28 Yue Chao, Lei Huang, Xuejun Ma, Jiajun Sun
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Moderate deviation principle of modularity in network Metrika (IF 0.7) Pub Date : 2023-06-16 Qing Yin, Yu Miao, Zhen Wang, Guangyu Yang
In the present paper, we study a specific partition of a given network and establish the moderate deviation principle of modularity for the partition when the size of the network gets large.
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On Bernoulli trials with unequal harmonic success probabilities Metrika (IF 0.7) Pub Date : 2023-06-08 Thierry Huillet, Martin Möhle
A Bernoulli scheme with unequal harmonic success probabilities is investigated, together with some of its natural extensions. The study includes the number of successes over some time window, the times to (between) successive successes and the time to the first success. Large sample asymptotics, statistical parameter estimation, and relations to Sibuya distributions and Yule–Simon distributions are
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Nonparametric estimation of univariate and bivariate survival functions under right censoring: a survey Metrika (IF 0.7) Pub Date : 2023-06-05 Paul Janssen, Noël Veraverbeke
Survival analysis studies time to event data, also called survival data in biomedical research. The main challenge in the analysis of survival data is to develop inferential methods that take into account the incomplete information contained in censored observations. The seminal paper of Kaplan and Meier (J Am Stat Assoc 53:457–481,1958) gave a boost to the development of statistical methods for time
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Asymptotic distributions for likelihood ratio tests for the equality of covariance matrices Metrika (IF 0.7) Pub Date : 2023-06-02 Wenchuan Guo, Yongcheng Qi
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A note on asymptotics of the risk function under confidence region estimation in case of large samples of random size Metrika (IF 0.7) Pub Date : 2023-05-24 Alexander Zaigraev
The problem of optimal estimation of location and scale parameters of absolutely continuous distributions, by means of two-dimensional confidence regions based on L-statistics, is considered. The case, when the sample size is random and tends to infinity, is studied. The paper can be considered as a supplement to Zaigraev and Alama-Bućko (Metrika 81:283–305, 2018) in case of samples of random size
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On the number of failed components in a series–parallel system upon system failure when the lifetimes are DNID discrete random variables Metrika (IF 0.7) Pub Date : 2023-05-25 Krzysztof Jasiński
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Poisson generalized Lindley process and its properties Metrika (IF 0.7) Pub Date : 2023-05-17 Ji Hwan Cha, F. G. Badía
In spite of the practical usefulness of the nonhomogeneous Poisson process, it still has some restrictions. To overcome these restrictions, the Poisson Lindley process has been recently developed and introduced in Cha (Stat Probab Lett 152: 74–81, 2019). In this paper, we further generalize the Poisson Lindley process, so that the developed counting process model should have the restarting property
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Optimal two-level regular fractional factorial split-plot designs when the effects of subplot factors are more important Metrika (IF 0.7) Pub Date : 2023-05-05 Haosheng Jiang, Chongqi Zhang
Robust parameter design (RPD) is an engineering methodology that focuses on reducing the variation of a process by appropriately selecting the setting of its control factors so as to make it less sensitive to noise variation. Then control factors are crucial in achieving robustness. If the control factors and noise factors in such a design are treated as the sub-plot (SP) factors and whole plot factors
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Comparison of extreme order statistics from two sets of heterogeneous dependent random variables under random shocks Metrika (IF 0.7) Pub Date : 2023-04-26 Ebrahim Amini-Seresht, Ebrahim Nasiroleslami, Narayanaswamy Balakrishnan
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Real-time changepoint detection in a nonlinear expectile model Metrika (IF 0.7) Pub Date : 2023-03-30 Gabriela Ciuperca, Matúš Maciak, Michal Pešta
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Estimation and bootstrap for stochastically monotone Markov processes Metrika (IF 0.7) Pub Date : 2023-02-28 Michael H. Neumann
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Kernel regression for estimating regression function and its derivatives with unknown error correlations Metrika (IF 0.7) Pub Date : 2023-02-22 Liu Sisheng, Yang Jing
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Distributed estimation of functional linear regression with functional responses Metrika (IF 0.7) Pub Date : 2023-02-22 Jiamin Liu, Rui Li, Heng Lian
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Robust nonparametric equivariant regression for functional data with responses missing at random Metrika (IF 0.7) Pub Date : 2023-02-13 Omar Fetitah, Mohammed Kadi Attouch, Salah Khardani, Ali Righi
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Characterization of three-order confounding via consulting sets Metrika (IF 0.7) Pub Date : 2023-02-13 Chongya Yan, Zhiming Li, Mingyao Ai
The aliased effect-number pattern, proposed by Zhang et al. (Stat Sin 18:1689–1705, 2008), is often used to express the overall confounding between factorial effects in two-level regular designs. The confounding relationships of main effects and two-factor interactions have been well revealed in literature, but little is known about three and higher-order interactions. To fill the gaps, this paper