Communication in Statistics- Theory and Methods (COMMUN STAT-THEOR M )

Publisher: Taylor & Francis

Description

The Theory and Methods series intends to publish papers that make theoretical and methodological advances in Probability and Statistics. New applications of statistical and probabilistic methods will also be considered for publication. In addition, special issues dedicated to a specific topic of current interest will also be published in this series periodically, providing an exhaustive and up-to-date review of that topic to the readership.

Impact factor 0.28

  • Hide impact factor history
     
    Impact factor
  • 5-year impact
    0.43
  • Cited half-life
    0.00
  • Immediacy index
    0.05
  • Eigenfactor
    0.01
  • Article influence
    0.29
  • Website
    Communications in Statistics - Theory and Methods website
  • Other titles
    Communications in statistics, theory and methods (Online), Communications in statistics, theory and methods, Theory and methods
  • ISSN
    0361-0926
  • OCLC
    48483352
  • Material type
    Document, Periodical, Internet resource
  • Document type
    Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

Taylor & Francis

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author can archive a post-print version
  • Conditions
    • Some individual journals may have policies prohibiting pre-print archiving
    • On author's personal website or departmental website immediately
    • On institutional repository or subject-based repository after either 12 months embargo for STM, Behavioural Science and Public Health Journals or 18 months embargo for SSH journals
    • Publisher's version/PDF cannot be used
    • On a non-profit server
    • Published source must be acknowledged
    • Must link to publisher version
    • Set statements to accompany deposits (see policy)
    • The publisher will deposit in on behalf of authors to a designated institutional repository including PubMed Central, where a deposit agreement exists with the repository
    • STM: Science, Technology and Medicine
    • SSH: Social Science and Humanities
    • Publisher last contacted on 25/03/2014
    • 'Taylor & Francis (Psychology Press)' is an imprint of 'Taylor & Francis'
  • Classification
    ​ green

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: In this article, we establish strong consistency of the ridge estimates using extended results for the strong consistency of the least squares estimates in multiple regression models which discard the usual assumption of null mean value for the errors and only requires them to be i.i.d. with absolute moment of order r (0 r 1).
    Communication in Statistics- Theory and Methods 02/2015; 44(3).
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    ABSTRACT: We study an extended form of exponential smoothing which is more flexible than the original one: let be a real stochastic process, observed until time n, consider the probabilistic predictor of X n + 1 defined as where the series is supposed to be convergent in mean square. We look for stochastic models such that X*n + 1 is the best linear predictor of X n + 1, given Xt, t n. We obtain various ARIMA models depending on (α, β). In this context we study estimation of (α, β) and give some indications concerning hypotheses testing. Finally, extension to functional stochastic processes is considered.
    Communication in Statistics- Theory and Methods 02/2015; 44(3).
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    ABSTRACT: Based on free-knot splines techniques, we develop a fully Bayesian method to make inference about the autoregressive and functional-coefficient moving-average models, including estimation and prediction. We approximate different functional-coefficients by polynomial splines with different orders to adapt to different smoothness. To make the estimation and prediction robust, we assign heavy-tailed student-t priors on the coefficients of both the splines and the autoregressive terms. The posterior predictive distribution is derived from a Bayesian model average over all of the possible models. The proposed method is demonstrated by both simulated and real data examples.
    Communication in Statistics- Theory and Methods 02/2015; 44(3).
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    ABSTRACT: Here we consider a new class of asymmetric normal distributions as a generalization of the skew normal distribution of Azzalini (1985) and the skew generalized normal distribution of Arellano-Valle et al. (2004). Several properties of this new class of distributions are derived and there by obtained the corresponding properties of the location scale extended family of the new class of distributions. The estimation of the parameters of the location scale extended class of distributions is also briefly discussed.
    Communication in Statistics- Theory and Methods 02/2015; 44(3).
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    ABSTRACT: Phillips and Magdalinos (2007) introduced a larger neighborhoods of one (called moderate deviations) than the conventional local to unity roots in autoregression models. Least square estimates (LSE) of the serial correlation coefficient were studied and asymptotics were provided. In this article, we investigate the M-estimation of the serial correlation coefficient having moderate deviations from the unit root. For both the near stationary case and explosive case, the Bahadur representations and limits in distribution are given for the M-estimators of the serial correlation coefficient. The limit theory demonstrates that the convergence rates of the M-estimators are the same as that for LSE hence bridging the very different convergence rates of the stationary and unit root cases. The limit theory also facilitates the comparison of the relative asymptotic efficiency among different estimators within the family of M-estimators.
    Communication in Statistics- Theory and Methods 02/2015; 44(3).
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    ABSTRACT: Continuous mixture Weibull models arise in many areas of sciences such as reliability studies, communications theory, etc. Due to its wide applicability, we introduce a class of continuous mixture Weibull models which is a combination of Weibull and generalized gamma distributions. Some characteristics of the distribution are obtained. It is seen that Krätzel integral enters into the model naturally, and then the model can be called as a Krätzel density. Applications of the density function related to fading channels and ultrasonic backscatter signals modeling are discussed. A real data analysis is given to illustrate the use of this distribution.
    Communication in Statistics- Theory and Methods 01/2015; 44(2).
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    ABSTRACT: We study moderate deviations of estimators of financial risk under an asymmetric Laplace law. The moderate deviation principles of two kinds of estimators of Value-at-Risk (VaR) and conditional Value-at-Risk (CVaR) are obtained by the approximation method and the delta method in large deviations. Some numerical comparisons of the estimators are also presented.
    Communication in Statistics- Theory and Methods 01/2015; 44(2).
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    ABSTRACT: The distribution of correlated variance ratio arises if variables in the parent population are correlated. One such case arises if sample observations follow independent bivariate normal distributions. We study its cumulative distribution function, raw moments, mean centered moments, coefficient of skewness and kurtosis, median and reliability. The density function is also graphed. We address the issue of the invariance of the distribution of correlated variance ratio, and testing equality of variances under correlation. Finally we exhibit an application of the said distribution in quality control problems for monitoring process outputs using control charts.
    Communication in Statistics- Theory and Methods 01/2015; 44(2).
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    ABSTRACT: The confidence level of the usual interval for a ratio of variance components is contingent on normally distributed random variables. In this article we focus on confidence intervals for ratios of variance components in balanced one-way random effects models based on the large-sample properties of restricted maximum likelihood (REML) estimators. While this procedure does not require that the random variables be normally distributed, one must estimate a parameter that is a function of the kurtosis of the underlying distributions. Simulation results indicate that REML-based confidence interval methods outperform other well-known methods in the majority of the cases considered.
    Communication in Statistics- Theory and Methods 01/2015; 44(2).
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    ABSTRACT: In this article, we establish a new complete convergence theorem for weighted sums of negatively dependent random variables. As corollaries, many results on the almost sure convergence and complete convergence for weighted sums of negatively dependent random variables are obtained. In particular, the results of Jing and Liang (2008), Sung (2012), and Wu (2010) can be obtained.
    Communication in Statistics- Theory and Methods 01/2015; 44(2).
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    ABSTRACT: Three variations of partially replicated central composite designs have been compared. Their prediction capabilities with respect to their prediction variances are assessed using variance dispersion graphs in cuboidal region when the axial distance is α = 1. The results show that for n 0 = 1, 2, and 3 center points, the replicated star designs have better prediction potentials than the replicated cube designs when interest is in predicting responses in the face-centered cube. The face-centered cube is the second-order central composite design with axial distance, α = 1.
    Communication in Statistics- Theory and Methods 01/2015; 44(2).
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    ABSTRACT: Birnbaum and Saunders (1969a) pioneered a lifetime model which is commonly used in reliability studies. Based on this distribution, a new model called the gamma-Birnbaum-Saunders distribution is proposed for describing fatigue life data. Various properties of the new distribution including explicit expressions for the ordinary and incomplete moments, generating and quantile functions, mean deviations, density function of the order statistics and their moments are derived. We discuss the method of maximum likelihood and a Bayesian approach to fit the model parameters. The superiority of the new model is illustrated by means of three failure real data sets. We also propose a new extended regression model based on the logarithm of the new distribution. This last model can be very useful to the analysis of real data and provide more realistic fits than other special regression models.
    Communication in Statistics- Theory and Methods 01/2015;
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    ABSTRACT: For the exploratory analysis of three-way data, the Tucker3 is one of the most applied models to study three-way arrays when the data are approximately trilinear. When the data consist of vectors of positive values summing to a unit, as in the case of compositional data, this model should consider the special problems that compositional data analysis brings. The principal purpose of this paper is to describe how to do a Tucker3 analysis of compositional data, and to show the relationships between the loadings matrices when different preprocessing procedures are used.
    Communication in Statistics- Theory and Methods 01/2015;
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    ABSTRACT: Recently, a procedure was developed for constructing 100(1–α)% confidence ellipses for points in a low-dimensional plot obtained from performing classical correspondence analysis. This article reviews the construction of confidence regions for classical and non symmetric correspondence analysis and proposes a simple procedure for determining p-values of each of the points in this space. Such features enable the researcher to determine the statistical significance of a category to the association structure between the categorical variables being analyzed. They also reflect the information contained in dimensions higher than those that typically allow for a visual inspection of the association structure.
    Communication in Statistics- Theory and Methods 01/2015; 44(1).
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    ABSTRACT: In this paper we develop the methodology for designing clinical trials with any factorial arrangement when the primary outcome is time to event. We provide a matrix formulation for calculating the sample size and study duration necessary to test any effect with a pre-specified type I error rate and power. Assuming that a time to event follows an exponential distribution, we describe the relationships between the effect size, the power, and the sample size. We present examples for illustration purposes. We provide a simulation study to verify the numerical calculations of the expected number of events and the duration of the trial. The change in the power produced by a reduced number of observations or by accruing no patients to certain factorial combinations is also described.
    Communication in Statistics- Theory and Methods 01/2015; 44(2):275-285.
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    ABSTRACT: In this paper, we propose new estimation techniques in connection with the system of S-distributions. Besides “exact” maximum likelihood (ML), we propose simulated ML and a characteristic function-based procedure. The “exact” and simulated likelihoods can be used to provide numerical, MCMC-based Bayesian inferences.
    Communication in Statistics- Theory and Methods 01/2015; 44(1).
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    ABSTRACT: Cossette et al. (2010, 2011) gave a novel collective risk model where the total numbers of claims satisfy the first-order integer-valued autoregressive process. For a risk model, it is interesting to investigate the upper bound of ruin probability. However, the loss increments of the above model are dependent; it is difficult to derive the upper bound of ruin probability. In this article, we propose an approximation model with stationary independent increments. The upper bound of ruin probability and the adjustment coefficient are derived. The approximation model is illustrated via four simulated examples. Results show that the gap of the approximation model and dependent model can be ignored by adjusting values of parameters.
    Communication in Statistics- Theory and Methods 12/2014; 43(24).
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    ABSTRACT: In this paper, we study the estimators of two measures of dependence: the signed symmetric covariation coefficient (scov) proposed by Garel and Kodia and the generalized association parameter (g.a.p.) put forward by Paulauskas. In the sub-Gaussian case, the scov and the g.a.p. coincide. The estimator of the scov proposed here is based on fractional lower-order moments. The estimator of the g.a.p. is based on estimation of a stable spectral measure. We investigate the relative performance of these estimators by comparing results from simulations.
    Communication in Statistics- Theory and Methods 12/2014; 43(24).