Maleki, M.,
Arellano-valle, R.B.,
Dey, D.K.,
Mahmoudi, M.,
Jalali, S.M.J. Publication Date: 2017
Calcutta Statistical Association Bulletin (00080683)69(2)pp. 165-182
This article studies autoregressive (AR) models assuming innovations with scale mixtures of skew-normal (SMSN) distributions, an attractive and flexible family of probability distributions. A Bayesian analysis considering informative prior distributions is presented. Comprehensive simulation studies are performed to support the performance of the proposed model and methods. The proposed methods are also applied on a real-time series data which has previously been analysed under Gaussian and Student-t AR models. © 2018 Calcutta Statistical Association, Kolkata.
Publication Date: 2021
Journal of Applied Statistics (02664763)48(6)pp. 1071-1090
In this paper, a new bivariate discrete generalized exponential distribution, whose marginals are discrete generalized exponential distributions, is studied. It is observed that the proposed bivariate distribution is a flexible distribution whose cumulative distribution function has an analytical structure. In addition, a new bivariate geometric distribution can be obtained as a special case. We study different properties of this distribution and propose estimation of its parameters. We will see that the maximum of the variables involved in the proposed bivariate distribution defines some new classes of univariate discrete distributions, which are interesting in their own sake, and can be used to analyze some Reliability systems whose components are positive dependent. Some important futures of this new univariate family of discrete distributions are also studied in details. In addition, a general class of bivariate discrete distributions, whose marginals are exponentiated discrete distributions, is introduced. Moreover, the analysis of two real bivariate data sets is performed to indicate the effectiveness of the proposed models. Finally, we conclude the paper. © 2020 Informa UK Limited, trading as Taylor & Francis Group.
Publication Date: 2026
Aut Journal Of Mathematics And Computing (27832449)7(1)pp. 1-18
In this paper, some general classes of bivariate semi-parametric continuous distributions are introduced. Some important properties of this family of distributions will be illustrated. It is seen that the bivariate distribution corresponds to the known Ali-Mikhail-Haq copula. Hence, some important properties such as the TP2 property are justified. It will be shown that the marginals are kind of heavy tailed weighted distributions whose hazard rate functions can take variety of shapes. The behavior of the hazard rate function is mathematically illustrated. In addition, the α-power transformed distributions of a second type, which are introduced for the first time here, can be verified as special cases of the marginals. Some members of the new bivariate classes are studied in details. The estimation of the parameters is illustrated by means of an efficient expectation-maximization algorithm, and some real data sets are also analyzed for illustrative purposes. © 2026 The Author(s).
Publication Date: 2025
Computational Statistics (09434062)40(3)pp. 1147-1170
Extensions of quantile regression modeling for time series analysis are extensively employed in medical and health studies. This study introduces a specific class of transformed quantile-dispersion regression models for non-stationary time series. These models possess the flexibility to incorporate the time-varying structure into the model specification, enabling precise predictions for future decisions. Our proposed modeling methodology applies to dynamic processes characterized by high variation and possible periodicity, relying on a non-linear framework. Additionally, unlike the transformed time series model, our approach directly interprets the regression parameters concerning the initial response. For computational purposes, we present an iteratively reweighted least squares algorithm. To assess the performance of our model, we conduct simulation experiments. To illustrate the modeling strategy, we analyze time-series measurements of influenza infection and daily COVID-19 deaths. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.
Publication Date: 2017
Journal of Statistical Computation and Simulation (15635163)87(1)pp. 171-186
In this paper, we investigate estimation methods to deal with situations where random intercepts are associated to time-varying covariates in the context of linear mixed models. First, a review of previous ways to deal with this so-called endogeneity issue is presented, then a new method based on shared random effects is proposed. Simulation studies and an empirical example are utilized to assess the performance of our proposed method. It is shown that our new approach is more efficient than most competitors and is robust to the misspecification of the random-effects distributions. © 2016 Informa UK Limited, trading as Taylor & Francis Group.
Publication Date: 2011
Computational Statistics and Data Analysis (01679473)55(1)pp. 578-587
Efron (1979) introduced the bootstrap method for independent data but it cannot be easily applied to spatial data because of their dependency. For spatial data that are correlated in terms of their locations in the underlying space the moving block bootstrap method is usually used to estimate the precision measures of the estimators. The precision of the moving block bootstrap estimators is related to the block size which is difficult to select. In the moving block bootstrap method also the variance estimator is underestimated. In this paper, first the semi-parametric bootstrap is used to estimate the precision measures of estimators in spatial data analysis. In the semi-parametric bootstrap method, we use the estimation of the spatial correlation structure. Then, we compare the semi-parametric bootstrap with a moving block bootstrap for variance estimation of estimators in a simulation study. Finally, we use the semi-parametric bootstrap to analyze the coal-ash data. © 2010 Elsevier B.V. All rights reserved.
Publication Date: 2017
Electronic Journal of Applied Statistical Analysis (20705948)10(2)pp. 349-373
There is abundant and increasing evidence that the lognormal distribution can account for random variation present in the data from many scientific fields. In the light of this exibility for modeling, this article deals with goodness-of-fit tests for the lognormal distribution. Several testing procedures are compared by means of extensive simulation. Lastly, an actuarial data set is analyzed for illustration. © Universitá del Salento.
Publication Date: 2022
Statistical Modelling (1471082X)22(4)pp. 327-348
This article introduces a flexible modelling strategy to extend the familiar mixed-effects models for analysing longitudinal responses in the multivariate setting. By initiating a flexible multivariate multimodal distribution, this strategy relaxes the imposed normality assumption of related random-effects. We use copulas to construct a multimodal form of elliptical distributions. It can deal with the multimodality of responses and the non-linearity of dependence structure. Moreover, the proposed model can flexibly accommodate clustered subject-effects for multiple longitudinal measurements. It is much useful when several subpopulations exist but cannot be directly identifiable. Since the implied marginal distribution is not in the closed form, to approximate the associated likelihood functions, we suggest a computational methodology based on the Gauss–Hermite quadrature that consequently enables us to implement standard optimization techniques. We conduct a simulation study to highlight the main properties of the theoretical part and make a comparison with regular mixture distributions. Results confirm that the new strategy deserves to receive attention in practice. We illustrate the usefulness of our model by the analysis of a real-life dataset taken from a low back pain study. © 2020 Statistical Modeling Society.
Publication Date: 2012
Communications in Statistics - Theory and Methods (1532415X)41(11)pp. 2000-2013
In this article, we attempt to introduce a discrete analog of the generalized exponential distribution of Gupta and Kundu (1999). This new discrete generalized exponential (DGE(, p)) distribution can be viewed as another generalization of the geometric distribution and it is more flexible in data modeling. We shall first study some basic distributional and moment properties of this family of new distributions. Then, we will reveal their structural properties and applications and also investigate estimation of their parameters. Finally, we shall discuss their convolution properties and arrive at some characterizations in the special cases DGE(2, p) and DGE(3, p). © 2012 Taylor and Francis Group, LLC.
Publication Date: 2022
Journal of Statistical Physics (00224715)189(1)
We study a system of coalescing random walks on the integer lattice Zd in which the walk is oriented in the d-th direction and follows certain specified rules. We first study the geometry of the paths and show that, almost surely, the paths form a graph consisting of just one tree for dimensions d= 2 , 3 and infinitely many disjoint trees for dimensions d≥ 4. Also, there is no bi-infinite path in the graph almost surely for d≥ 2. Subsequently, we prove that for d= 2 the diffusive scaling of this system converges in distribution to the Brownian web. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Publication Date: 2022
Statistics (02331888)56(1)pp. 147-163
This paper introduces a dynamic divergence measure to assess the discrepancy between the distribution functions of two inactivity lifetime random variables. Various time-dependent results on the proposed divergence measure in connection to other well-known measures in reliability engineering and survival studies are investigated. Some aging and monotonicity properties of such a measure are also studied. Furthermore, the proposed criterion is examined in two general classes of transformation models which results in some well-known models in the lifetime studies and survival analysis. © 2022 Informa UK Limited, trading as Taylor & Francis Group.
Publication Date: 2019
Test (11330686)28(2)pp. 543-564
In this paper, we consider a linear mixed effect model (LMM) assuming that the random effect and error terms follow an unrestricted skew-normal generalized-hyperbolic (SUNGH) distribution. The SUNGH is a broad class of flexible distributions that includes various other well-known asymmetric and symmetric families and provides a high degree of flexibility for the modeling of complex multivariate data with different directions and degrees of asymmetry, kurtosis and heavy tails. The choice of the best fitting distribution can proceed quite naturally through parameter estimation or by placing constraints on specific parameters and assessing using model choice criteria. We estimate parameters of the LMM using a Bayesian approach and examine the performance of the proposed methodology on simulated and real data from a clinical trial on treatment options for schizophrenia (Lapierre et al. Acta Psychiatric Scandinavica 82:72–76, 1990; Ho and Lin Biom J 52(4):449–469, 2010). © 2018, Sociedad de Estadística e Investigación Operativa.
Publication Date: 2023
Ricerche di Matematica (18273491)72(2)pp. 1-36
In this paper, we propose a flexible growth model that constitutes a suitable generalization of the well-known Gompertz model. We perform an analysis of various features of interest, including a sensitivity analysis of the initial value and the three parameters of the model. We show that the considered model provides a good fit to some real datasets concerning the growth of the number of individuals infected during the COVID-19 outbreak, and software failure data. The goodness of fit is established on the ground of the ISRP metric and the d2 -distance. We also analyze two time-inhomogeneous stochastic processes, namely a birth-death process and a birth process, whose means are equal to the proposed growth curve. In the first case we obtain the probability of ultimate extinction, being 0 an absorbing endpoint. We also deal with a threshold crossing problem both for the proposed growth curve and the corresponding birth process. A simulation procedure for the latter process is also exploited. © 2020, The Author(s).
Kelishadi, R.,
Heidari, Z.,
Kazemi, I.,
Jafari-koshki, T.,
Mansourian, M.,
Motlagh, M.,
Heshmat, R. Publication Date: 2018
Journal of Pediatric Endocrinology and Metabolism (0334018X)31(4)pp. 443-449
This study aimed to assess determinants of anthropometric measures in a nationally representative sample of Iranian children and adolescents. This nationwide study was conducted among 13,280 students, aged 6-18 years, who were randomly selected from 30 provinces in Iran. Anthropometric measures were determined by calibrated instruments. Demographic and socio-economic (SES) variables, lifestyle behaviors, family history of chronic disease and prenatal factors were studied, as well. A hierarchical Bayesian tri-variate analysis was used to assess the factors associated with obesity measures of the body mass index (BMI), waist-to-height ratio (WHtR) and wrist circumference (WrC). The results showed that the BMI was associated with SES score, family history of obesity, family history of diabetes mellitus, physical inactivity, screen time, duration of sleep, breakfast consumption, birth weight, breastfeeding, junk food and place of residence (urban-rural). All these factors were also significantly associated with WrC except for consumption of junk food. Many of these factors had a partial but significant relationship with WHtR. Various factors contribute to obesity. Preventive and educational programs on manageable factors such as increasing physical activity, eating breakfast and limiting TV or screen time could be helpful in controlling obesity in schoolchildren and reducing associated complications. © 2018 Walter de Gruyter GmbH, Berlin/Boston.
Publication Date: 2018
Metron (00261424)76(1)pp. 115-131
In the present paper, we define a new measure of divergence between two probability distribution functions F1 and F2 based on Jensen inequality and Gini mean difference. The proposed measure, which we call it Jensen–Gini measure of divergence (JG), is symmetric and its square root is a metric. We show that the JG can be represented as a mixture of Cramér’s distance (CD) between the two distributions F1 and F2. A generalization of JG for measuring the overall difference between several probability distributions is also proposed. The proposed JG measure of divergence is applied to estimate the unknown parameters of a probability distribution. We consider a statistical model F(x; θ) , where the parameter θ∈ Θ is assumed to be unknown. Based on a random sample drawn from the distribution, we consider the JG between the distribution F(x; θ) and the empirical estimator of the distribution. Then, we estimate the parameter θ as a value in the parameter space Θ which minimizes the JG between the distribution F(x; θ) and its empirical estimator. We call this estimator as minimum Jensen–Gini estimator (MJGE) of the parameter. Several properties of MJGE are investigated. It is shown that the MJGE is in the class of generalized estimating equations. Asymptotic properties of MJGE such as consistency and normality are explored. Some simulation studies are performed to evaluate the performance of MJGE. © 2017, Sapienza Università di Roma.
Sharifonnasabi, Z.,
Alamatsaz m.h., M.H.,
Kazemi, I. Publication Date: 2018
Brazilian Journal of Probability and Statistics (01030752)32(3)pp. 497-524
In this paper, we shall construct a large class of new bivariate copulas. This class happens to contain several known classes of copulas, such as Farlie–Gumbel–Morgenstern, Ali–Mikhail–Haq and Barnett–Gumbel, as its especial members. It is shown that the proposed copulas improve the range of values of correlation coefficient and thus they are more applicable in data modeling. We shall also reveal that the dependent properties of the base copula are preserved by the generated copula under certain conditions. Several members of the new class are introduced as instances and their range of correlation coefficients are computed. © Brazilian Statistical Association, 2018.
Maleki, M.,
Mclachlan, G.J.,
Gurewitsch r., ,
Aruru m., ,
Pyne, S. Publication Date: 2020
Statistics and Applications (24547395)18(1)pp. 295-306
As the COVID-19 pandemic spread worldwide, it has become clearer that prevalence of certain comorbidities in a given population could make it more vulnerable to serious outcomes of that disease, including fatality. Indeed, it might be insightful from a health policy perspective to identify clusters of populations in terms of the associations between their prevalent comorbidities and the observed COVID-19 specific death rates. In this study, we described a mixture of polynomial time series (MoPTS) model to simultaneously identify (a) three clusters of 86 U.S. cities in terms of their dynamic death rates, and (b) the different associations of those rates with 5 key comorbidities among the populations in the clusters. We also described an EM algorithm for efficient maximum likelihood estimation of the model parameters. © 2020, Society of Statistics, Computer and Applications. All rights reserved.
Publication Date: 2017
Statistics and Probability Letters (01677152)129pp. 28-33
We propose a new estimator for the population proportion using a concomitant-based ranked set sampling (RSS) scheme. Simulation results show that the new estimator beats the standard estimator in the RSS as long as the ranking quality is fairly good. © 2017 Elsevier B.V.
Publication Date: 2023
IET Science, Measurement and Technology (17518822)17(9)pp. 351-360
Low-frequency noise, generated inherently by the number or mobility fluctuation of carriers, is a crucial concern for the design of analog and digital circuits. Unified modelling based on experimental validation of near-DC noise in amplifiers is a long-standing open problem. This article develops a model for low-frequency noise by deriving new bounds for carrier capturing and releasing. According to the proposed model, a measurement system is suggested that operates in a wide frequency range and even at very low frequencies. The system is noise-tolerant, since the amplifier is selected based on acceptable noise levels. Among the advantages are the independence from specialized structural noise models for each component and the low cost of the measurement system. The evaluation results show that the proposed method leads to a promising improvement in the low-frequency noise measuring and is superior to conventional models in the normalized root mean square error indicator. Findings reveal that the proposed measurement method can estimate the flicker noise around the DC frequency, and the proposed model agrees reasonably with the proposed measurement circuit. © 2023 The Authors. IET Science, Measurement & Technology published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.
Publication Date: 2025
Journal of Statistical Theory and Practice (15598616)19(2)
In this paper, another motivation for the well-known quadratic transmuted family of distributions is pointed out and a new relation for the expected value of this family in terms of the Gini index is presented. A bug of the generalized transmuted-G family of distributions Nofal et al. (Commun Stat Theory Methods 46:4119–4136, 2016) is illustrated. In that work, the necessary conditions for the density and distribution functions are not satisfied, for some parameter values. Moreover, a new flexible family of distributions is introduced from a fresh perspective, and their key properties are studied in general forms. As an example, a new high flexible distribution is introduced and some of its important futures such as the moment generating function, moments, order statistics and the stress-strength parameter are investigated. In addition, the parameters of the proposed new distribution are estimated using the maximum likelihood method, and three real data sets are scrutinized to assess the distribution’s adequacy in providing satisfactory fits. © Grace Scientific Publishing 2025.
Publication Date: 2019
Journal of Statistical Planning and Inference (03783758)198pp. 91-104
Main effect plus one plans (MEP.1) search for a non-zero interaction effect and estimate it in addition to estimate all main effects. A new series of MEP.1 with 2f runs has been constructed and given in this research for 2f factorial experiments for all odd prime power f≥9. Designs in this series are more efficient in estimating the factorial effects than the previous existent MEP.1 with the same number of runs based on D-efficiency criterion. In contrast to the former designs with 2f runs, the D-efficiency of new proposed designs is increasing in f. © 2018 Elsevier B.V.
Publication Date: 2015
Journal of Applied Statistics (02664763)42(12)pp. 2654-2670
In this paper, a discrete counterpart of the general class of continuous beta-G distributions is introduced. A discrete analog of the beta generalized exponential distribution of Barreto-Souza et al. [2], as an important special case of the proposed class, is studied. This new distribution contains some previously known discrete distributions as well as two new models. The hazard rate function of the new model can be increasing, decreasing, bathtub-shaped and upside-down bathtub. Some distributional and moment properties of the new distribution as well as its order statistics are discussed. Estimation of the parameters is illustrated using the maximum likelihood method and, finally, the model with a real data set is examined. © 2015 Taylor & Francis.
Publication Date: 2017
Communications in Statistics - Theory and Methods (1532415X)46(9)pp. 4296-4310
In this paper, the researchers attempt to introduce a new generalization of the Weibull-geometric distribution. The failure rate function of the new model is found to be increasing, decreasing, upside-down bathtub, and bathtub-shaped. The researchers obtained the new model by compounding Weibull distribution and discrete generalized exponential distribution of a second type, which is a generalization of the geometric distribution. The new introduced model contains some previously known lifetime distributions as well as a new one. Some basic distributional properties and moments of the new model are discussed. Estimation of the parameters is illustrated and the model with two known real data sets is examined. © 2017 Taylor & Francis Group, LLC.
Publication Date: 2013
Communications in Statistics - Theory and Methods (1532415X)42(3)pp. 528-542
In this article, another version of the generalized exponential geometric distribution different to that of Silva et al. (2010) is proposed. This new three-parameter lifetime distribution with decreasing, increasing, and bathtub failure rate function is created by compounding the generalized exponential distribution of Gupta and Kundu (1999) with a geometric distribution. Some basic distributional properties, moment-generating function, rth moment, and Rényi entropy of the new distribution are studied. The model parameters are estimated by the maximum likelihood method and the asymptotic distribution of estimators is discussed. Finally, an application of the new distribution is illustrated using the two real data sets. © 2013 Copyright Taylor and Francis Group, LLC.
Publication Date: 2016
Statistics (02331888)50(1)pp. 139-156
A new three-parameter distribution with decreasing, increasing, bathtub-shaped and upside-down bathtub-shaped hazard rate function is proposed. The new distribution encompasses some previously known distributions as special cases. Basic mathematical properties of the new distribution (including the moment-generating function, moments, order statistics properties, Rényi entropy and stress–strength parameter) are derived. Its parameters are estimated by the method of maximum likelihood. An application is illustrated using a real data set. © 2015 Taylor & Francis.
Publication Date: 2017
Metrika (1435926X)80(6-8)pp. 649-661
We propose a new measure of association between two continuous random variables X and Y based on the covariance between X and the log-odds rate associated to Y. The proposed index of correlation lies in the range [- 1 , 1]. We show that the extremes of the range, i.e., - 1 and 1, are attainable by the Fre ´ chet bivariate minimal and maximal distributions, respectively. It is also shown that if X and Y have bivariate normal distribution, the resulting measure of correlation equals the Pearson correlation coefficient ρ. Some interpretations and relationships to other variability measures are presented. Among others, it is shown that for non-negative random variables the proposed association measure can be represented in terms of the mean residual and mean inactivity functions. Some illustrative examples are also provided. © 2017, Springer-Verlag GmbH Germany.
