Communication in Statistics- Theory and Methods (Comm Stat Theor Meth)

Publications in this journal

• Article: Robust Estimation of Multi-Response Surfaces Considering Correlation Structure

  Moslemi A, Bashiri M, Niaki STA
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  ABSTRACT: Response surfaces express the behavior of responses and can be used for both single and multi-response problems. A common approach to estimate a response surface using experimental results is the ordinary least squares (OLS) method. Since OLS is very sensitive to outliers, some robust approaches have been discussed in the literature. Although there are many methods available in the literature for multiple response optimizations, there are a few studies in model building especially robust models. Assuming correlated responses, in this paper, a robust coefficient estimation method is proposed for multi response problem based on M-estimators. In order to illustrate the performance of the proposed procedure, a contaminated experimental design using a numerical example available in the literature with some modifications is used. Both the classical multivariate least squares method and the proposed robust multivariate approach are used to estimate regression coefficients of multi-response surfaces based on this example. Moreover, a comparison of the proposed robust multi response surface (RMRS) approach with separate robust estimation of single response show that the proposed approach is more efficient.
  Communication in Statistics- Theory and Methods 12/2013;
• Article: Estimation of ratio of two finite-population means in the presence of non response

  Sarjinder Singh, Housila P. Singh, Rajesh Tailor, Mohammad Khoshnevisan, Marcin Kozak
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  ABSTRACT: We propose a wide class of estimators of the ratio of two finite-population means in the presence of random non response. Four estimators proposed by Toutenburg and Srivastava (1998) are shown as special cases of the proposed class of estimators. Linear models are developed to estimate the relative efficiency of the proposed class of estimators with respect to the above four estimators. Yes Yes
  Communication in Statistics- Theory and Methods 01/2013;
• Article: A GENERAL MODEL OF RANDOM VARIATION

  Haim Shore
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  ABSTRACT: A statistical distribution of a random variable is uniquely represented by its ‎normal-based quantile function. For a symmetrical distribution it is S-shaped (for ‎negative kurtosis) and inverted S-shaped (otherwise). As skewness departs from ‎zero, the quantile function gradually transforms into a monotone convex function ‎‎(positive skewness) or concave function (otherwise). Recently, a new general ‎modeling platform has been introduced, Response Modeling Methodology, which ‎delivers good representation to monotone convex relationships due to its unique ‎‎"continuous monotone convexity" property. In this paper, this property is ‎exploited to model the normal-based quantile function, and explored using a set ‎of 27 distributions. ‎
  Communication in Statistics- Theory and Methods 01/2013;
• Article: Functional form for the generalized Poisson regression model

  Zamani Hossein, Noriszura Ismail
  Communication in Statistics- Theory and Methods 08/2012;
• Article: Characterizations of Lifetime Distributions Based on Doubly Truncated Mean Residual Life and Mean Past to Failure

  M. Khorashadizadeh, A. H. Rezaei Roknabadi, G. R. Mohtashami Borzadaran
  Communication in Statistics- Theory and Methods 02/2012; 41(6):1105-1115.
• Article: Locally most powerful rank tests for comparison of two failure rates based on multiple Type-II censored data

  M.S.Chikkagoudar and B.S.Biradar
  Communication in Statistics- Theory and Methods 01/2012; 41:4315 - 4331.
• Article: About Birnbaum-Saunders distributions based on the Johnson system.

  Athayde, Azevedo, Leiva, Sanhueza
  Communication in Statistics- Theory and Methods 01/2012; 41:2061-2079.
• Article: Lack-of-fit Tests for Generalized Linear Models via Splines.

  Chin-Shang Li
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  ABSTRACT: Cubic B-splines are used to estimate the nonparametric component of a semiparametric generalized linear model. A penalized log-likelihood ratio test statistic is constructed for the null hypothesis of the linearity of the non-parametric function. When the number of knots is fixed, its limiting null distribution is the distribution of a linear combination of independent chi-squared random variables, each with one df. The smoothing parameter is determined by giving a specified value for its asymptotically expected value under the null hypothesis. A simulation study is conducted to evaluate its power performance; a real-life dataset is used to illustrate its practical use.
  Communication in Statistics- Theory and Methods 01/2012; 41(23):4240-4250.
• Article: Variable Double Acceptance Sampling Plans Using the Process Loss Functions

  Muhammad Aslam, C H Yen, C H Chang, Chi-Hyuck Jun, Munir Ahmad
  Communication in Statistics- Theory and Methods 01/2012; 41:3633-3647.
• Article: Two Stage Variables Acceptance Sampling Plans Using Process Loss Functions

  Muhammad Aslam, Ching-Ho Yen, Chia-Hao Chang, Chi-Hyuck Jun, Munir Ahmad, Mujahid Rasool
  Communication in Statistics- Theory and Methods 01/2012; 41:3633–3647.