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Akhbari, M.S. ,
Arizi, H.R. ,
Eskandari, H. ,
Bidram, H. اندازه گیری تربیتی (2252004X) (40)pp. 1-29
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.
Computational Statistics (09434062) 39(2)pp. 677-708
Multicollinearity among independent variables is one of the most common problems in regression models. The aftereffects of this problem, such as ill-conditioning, instability of estimators, and inflating mean squared error of ordinary least squares estimator (OLS), in the multivariate linear regression model (MLRM) are the same that of linear regression models. To combat multicollinearity, several approaches have been presented in the literature. Liu estimator (LE), as a well known estimator in this connection, has been used in linear, generalized linear, and nonlinear regression models by researchers in recent years. In this paper, for the first time, LE and jackknifed Liu estimator (JLE) are investigated in MLRM. To improve estimators in the sense of mean squared error, two known resampling methods, i.e., jackknife and bootstrap, are used. Finally, OLS, LE, and JLE are compared by a simulation study and also using a real data set, by resampling methods in MLRM. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022.
Journal of Applied Statistics (02664763) 50(11-12)pp. 2648-2662
In this paper, we develop a mixture of autoregressive (MoAR) process model with time varying and freely indexed covariates under the flexible class of two–piece distributions using the scale mixtures of normal (TP-SMN) family. This novel family of time series (TP-SMN-MoAR) models was used to examine flexible and robust clustering of reported cases of Covid-19 across 313 counties in the U.S. The TP-SMN distributions allow for symmetrical/ asymmetrical distributions as well as heavy-tailed distributions providing for flexibility to handle outliers and complex data. Developing a suitable hierarchical representation of the TP-SMN family enabled the construction of a pseudo-likelihood function to derive the maximum pseudo-likelihood estimates via an EM-type algorithm. © 2022 Informa UK Limited, trading as Taylor & Francis Group.
Communications in Statistics - Theory and Methods (1532415X) 51(24)pp. 8553-8578
Multi-collinearity among regressors and consequently ill-conditioning inflates the mean squared error (MSE) of the maximum likelihood estimator (MLE) of the parameters in a regression model. In recent years, the Liu estimator (LE) has been widely used in the literature to improve the regression models. Since in some regression models, the dependent variable follows a double bounded distribution, such as the beta and Kumaraswamy distributions, we are going to consider these two regression models in the presence of a multi-collinearity problem with investigation of their properties, characterizations, MLEs, and LEs. Finally, MSEs of LEs and MLEs are compared under various link functions, using simulation and two real data sets. © 2021 Taylor & Francis Group, LLC.
This study focuses on the prevalence of COVID-19 disease along with vaccination in the United States. We have considered the daily total infected cases of COVID-19 with total vaccinated cases as exogenous input and modeled them using light/heavy tailed auto-regressive with exogenous input model based on the innovations that belong to the flexible class of the two-piece scale mixtures of normal (TP-SMN) family. We have shown that the prediction of COVID-19 spread is affected by the rate of vaccine injection. In fact, the presence of exogenous input variables in time series models not only increases the accuracy of modeling, but also causes better and closer approximations in some issues including predictions. An Expectation-Maximization (EM) type algorithm has been considered for finding the maximum likelihood (ML) estimations of the model parameters, and modeling as well as predicting the infected numbers of COVID-19 in the presence of the vaccinated cases in the US. © 2022 The Author(s).
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.
Mathematica Slovaca (01399918) 71(6)pp. 1581-1598
The main aim of this paper is to introduce a new class of continuous generalized exponential distributions, both for the univariate and bivariate cases. This new class of distributions contains some newly developed distributions as special cases, such as the univariate and also bivariate geometric generalized exponential distribution and the exponential-discrete generalized exponential distribution. Several properties of the proposed univariate and bivariate distributions, and their physical interpretations, are investigated. The univariate distribution has four parameters, whereas the bivariate distribution has five parameters. We propose to use an EM algorithm to estimate the unknown parameters. According to extensive simulation studies, we see that the effectiveness of the proposed algorithm, and the performance is quite satisfactory. A bivariate data set is analyzed and it is observed that the proposed models and the EM algorithm work quite well in practice. © 2021 Mathematical Institute Slovak Academy of Sciences.
Talebnejad, A. ,
Ranjbarian, B. ,
Bidram, H. ,
Samavatian, H. International Journal of Business Excellence (17560055) 19(1)pp. 16-42
Archetypal branding is a prolific yet underdeveloped field of study. To help in leveraging visual cues for transferring archetypal meanings of brand to consumers, this study explores the colour associations of archetypes. It also identifies how Iranian consumers perceive the well-known archetypes. Moreover, the associations of colour dimensions and colour-shape combinations with archetypes are investigated. In-depth interviews and a survey reveal that, in some archetypal perceptions, Iranians are rather different to western consumers. A joint effect of colour and shape on the visual associations of archetypes is also observed. Moreover, findings illustrate that not all colour attributes play a significant role in the perception of all archetypal characters. The results may form research propositions to be investigated in the future empirical studies. The results are helpful in brand building and brand meaning management. Copyright © 2019 Inderscience Enterprises Ltd.
Gazi University Journal Of Science (21471762) 32(4)pp. 1339-1354
In this paper, a new discrete distribution is introduced by compounding the geometric distribution with a zero truncated Poisson distribution, named geometric-zero truncated Poisson (GZTP) distribution. Some basic properties of the new distribution, such as the hazard rate function, moments, mode, median, etc., are studied. We show mathematically and numerically that the hazard rate function is increasing. The model parameters are estimated by the moment, least squared error and maximum likelihood methods. A simulation study is performed to compare the performance of the different estimators in terms of bias and mean squared error. An application of the new model is also illustrated using the three real data sets. © 2019, Gazi University Eti Mahallesi. All rights reserved.
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.
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.
Communications in Statistics - Theory and Methods (1532415X) 45(5)pp. 1575-1575
Hacettepe Journal of Mathematics and Statistics (2651477X) 45(6)pp. 1767-1779
In this paper, a new three-parameter extension of the generalized geo- metric distribution of [6] is introduced. The new discrete distribution belongs to the resilience parameter family and handles a decreasing, in- creasing, upside-down and bathtub-shaped hazard rate function. The new distributions can also be considered as discrete analogs of some recent continuous distributions belonging to the known Marshall-Olkin family. Here, some basic statistical and mathematical properties of the new distribution are studied. In addition, estimation of the unknown parameters, a simulated example and an application of the new model are illustrated. © 2016, Hacettepe University. All rights reserved.
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.
Information Systems Frontiers (15729419) 17(3)pp. 619-628
Large Information Systems (LISs) are integrated software packages organizations employed to manage one or whole aspects of their information flows inside and outside of their organization. Here, large integrated systems, which cover at least two aspects of organizational information flows, considered and tried to identify and rank Critical Success Factors (CSFs) of these systems during three major phases of LIS project. ERP literature used to shape the model of possible CSFs for LISs, and then the model surveyed by means of a questionnaire. Questionnaires data analysed to identify the importance and rank of each factor during the LIS life cycle. The results showed the top management support is the most critical CSF, and software package selection in pre-implementation stage is the most fundamental element during the LIS life cycle. © 2013, Springer Science+Business Media New York.
Communications in Statistics - Theory and Methods (1532415X) 44(10)pp. 2079-2091
There are not many known distributions for modeling discrete data. In this paper, we shall introduce a discrete analogue of the beta-exponential distribution of Nadarajah and Kotz (2006), which is more plausible in modeling discrete data and exhibits both increasing and decreasing hazard rates. The discrete beta-exponential distribution can be viewed as a generalization of the discrete generalized exponential distribution introduced by Nekoukhou et al. (2012) and, thus, as an another generalization of the geometric distribution. We shall first study some basic distributional and moment properties of the new distribution. Then, certain structural properties of the distribution such as its unimodality, hazard rate behavior, and Rényi entropy are discussed. Using the maximum likelihood method, estimation of the model parameters is also investigated. Finally, the model is examined with a real data set and compared with its rival model, that is, the discrete generalized exponential distribution. 2015 Copyright © Taylor & Francis Group, LLC.
Communications in Statistics Part B: Simulation and Computation (15324141) 44(6)pp. 1389-1404
In this article, the exponentiated Weibull distribution is extended by the Marshall-Olkin family. Our new four-parameter family has a hazard rate function with various desired shapes depending on the choice of its parameters and, thus, it is very flexible in data modeling. It also contains two mixed distributions with applications to series and parallel systems in reliability and also contains several previously known lifetime distributions. We shall study some basic distributional properties of the new distribution. Some closed forms are derived for its moment generating function and moments as well as moments of its order statistics. The model parameters are estimated by the maximum likelihood method. The stress-strength parameter and its estimation are also investigated. Finally, an application of the new model is illustrated using two real datasets. © 2015 Taylor & Francis Group, LLC.
SORT (16962281) 39(1)pp. 127-146
In this paper, the exponentiated discrete Weibull distribution is introduced. This new generalization of the discrete Weibull distribution can also be considered as a discrete analog of the exponentiated Weibull distribution. A special case of this exponentiated discrete Weibull distribution defines a new generalization of the discrete Rayleigh distribution for the first time in the literature. In addition, discrete generalized exponential and geometric distributions are some special sub-models of the new distribution. Here, some basic distributional properties, moments, and order statistics of this new discrete distribution are studied. We will see that the hazard rate function can be increasing, decreasing, bathtub, and upside-down bathtub shaped. Estimation of the parameters is illustrated using the maximum likelihood method. The model with a real data set is also examined.
Computational Statistics and Data Analysis (01679473) 74pp. 180-180
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.
Statistics (02331888) 47(4)pp. 876-887
In this paper, we shall attempt to introduce another discrete analogue of the generalized exponential distribution of Gupta and Kundu [Generalized exponential distributions, Aust. N. Z. J. Stat. 41(2) (1999), pp. 173-188], different to that of Nekoukhou et al. [A discrete analogue of the generalized exponential distribution, Comm. Stat. Theory Methods, to appear (2011)]. This new discrete distribution, which we shall call a discrete generalized exponential distribution of the second type (DGE2(α, p)), can be viewed as another generalization of the geometric distribution. We shall first study some basic distributional and moment properties, as well as order statistics distributions of this family of new distributions. Certain compounded DGE2(α, p) distributions are also discussed as the results of which some previous lifetime distributions such as that of Adamidis and Loukas [A lifetime distribution with decreasing failure rate, Statist. Probab. Lett. 39 (1998), pp. 35-42] follow as corollaries. Then, we will investigate estimation of the parameters involved. Finally, we will examine the model with a real data set. © 2013 Copyright Taylor and Francis Group, LLC.
SORT (16962281) 37(2)pp. 211-230
In this paper, we will introduce the new Kumaraswamy-power series class of distributions. This new class is obtained by compounding the Kumaraswamy distribution of Kumaraswamy (1980) and the family of power series distributions. The new class contains some new double bounded distributions such as the Kumaraswamy-geometric,-Poisson,-logarithmic and-binomial, which are used widely in hydrology and related areas. In addition, the corresponding hazard rate function of the new class can be increasing, decreasing, bathtub and upside-down bathtub. Some basic properties of this class of distributions such as the moment generating function, moments and order statistics are studied. Some special members of the class are also investigated in detail. The maximum likelihood method is used for estimating the unknown parameters of the members of the new class. Finally, an application of the proposed class is illustrated using a real data set.
Journal of Statistical Computation and Simulation (15635163) 83(1)pp. 52-67
A new five-parameter distribution called the beta Weibull-geometric (BWG) distribution is proposed. The new distribution is generated from the logit of a beta random variable and includes the Weibullgeometric distribution of Barreto-Souza et al. [TheWeibull-geometric distribution, J. Stat. Comput. Simul. 81 (2011), pp. 645–657], beta Weibull (BW), beta exponential, exponentiated Weibull, and some other lifetime distributions as special cases. A comprehensive mathematical treatment of this distribution is provided. The density function can be expressed as an infinite mixture of BW densities and then we derive some mathematical properties of the new distribution from the corresponding properties of the BW distribution. The density function of the order statistics and also estimation of the stress–strength parameter are obtained using two general expressions. To estimate the model parameters, we use the maximum likelihood method and the asymptotic distribution of the estimators is also discussed. The capacity of the new distribution are examined by various tools, using two real data sets. © 2013 Taylor & Francis.
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.
Communications in Statistics Part B: Simulation and Computation (15324141) 41(9)pp. 1606-1622
A new four-parameter distribution with decreasing, increasing, and upside-down bathtub failure rate called the beta exponential-geometric distribution is proposed. The new distribution, generated from the logit of a beta random variable, extends the exponential-geometric distribution of Adamidis and Loukas (1998) and some other distributions. A comprehensive mathematical treatment of this distribution is provided. Some expressions for the moment generating function, moments, order statistics, and Rényi entropy of the new distribution are derived. Estimation of the stress-strength parameter is also obtained. The model parameters are estimated by the maximum likelihood method and Fisher information matrix is discussed. Finally, an application to a real data set is illustrated. Copyright © Taylor & Francis Group, LLC.
Balali, G. ,
Hadi m.r., ,
Yavari p., ,
Bidram, H. ,
Naderi a.g., ,
Eslami a., African Journal of Biotechnology (16845315) 7(9)pp. 1265-1270
This study was carried out to evaluate the effects of pot size, planting date and type of genotype on mini-tuber production of Marfona potato cultivar (Solanum tuberosum L.) in greenhouse conditions. Four genotypes (M-129, M-128P, M-127P and M-124P) originated from virus free sprouts and a genotype of the same cultivar (Marfona) originated from apical meristem, in 3 sizes of pot and 3 planting date were investigated. The results showed that using larger pots of 3-liter has no advantage and pots smaller than 2-liter is not suitable for mini-tuber production. Also, time of Nov 18 was the best of date for planting of potato in studied conditions and delay in date of planting reduced the mini-tuber production. The reduction in number of mini-tubers and growing period was greater for the genotype M-129 compared with the other potato genotypes. Furthermore, higher numbers of mini-tubers were produced by the M-127P and M-124P genotypes and M-127P had the highest total weight of mini-tubers. However the number of mini-tubers per plant was higher for genotypes originated from meristem culture than genotypes obtained from sprouts. It seems that genotypes originated from potato sprouts are not as efficient as the apical meristem ones. On the other hand, later genotype showed more homogenous in growth rate and phenotype. © 2008 Academic Journals.
