@article{ author = {Jamalizadeh, Ahad and Amirzadeh, Vahid and Hashemi, Farzaneh}, title = {An Extension of the Birnbaum-Saunders Distribution Based on Skew-Normal t Distribution}, abstract ={In this paper, we introducte a family of univariate Birnbaum-Saunders distributions arising from the skew-normal-t  distribution. We obtain several properties of this distribution such as its moments, the maximum likelihood estimation procedure via an EM-algorithm and a method to evaluate standard errors using the EM-algorithm. Finally, we apply these methods to a real data set to demonstrate its flexibility and conduct a simulation study to demonstrate the usefulness of this distribution when compared to the ordinary Birnbaum-Saunders and skew-normal Birnbaum-Saunders distributions.}, Keywords = {EM and ECM algorithms, Monte Carlo simulations, observed information matrix, stochastic representation.}, volume = {12}, Number = {1}, pages = {1-37}, publisher = {Statistical Research and Training Center - Statistical Centre of Iran}, doi = {10.18869/acadpub.jsri.12.1.1}, url = {http://jsri.srtc.ac.ir/article-1-25-en.html}, eprint = {http://jsri.srtc.ac.ir/article-1-25-en.pdf}, journal = {Journal of Statistical Research of Iran JSRI}, issn = {2538-5771}, eissn = {2538-5763}, year = {2015} } @article{ author = {Emami, Hadi}, title = {Influence Measures in Ridge Linear Measurement Error Models}, abstract ={Usually the existence of influential observations is complicated by the presence of collinearity in linear measurement error models. However no method of influence measure available for the possible effect's that collinearity can have on the influence of an observation in such models. In this paper, a new type of ridge estimator based corrected likelihood function (REC) for linear measurement error models is defined. We show when this type of ridge estimator is used to mitigate the effects of collinearity the influence of some observations can be drastically modified. We propose a case deletion formula to detect influential points in REC. As an illustrative example two real data set are analysed. }, Keywords = {Corrected likelihood, diagnostics, leverage, measurement error models, shrinkage estimators.}, volume = {12}, Number = {1}, pages = {39-56}, publisher = {Statistical Research and Training Center - Statistical Centre of Iran}, doi = {10.18869/acadpub.jsri.12.1.39}, url = {http://jsri.srtc.ac.ir/article-1-23-en.html}, eprint = {http://jsri.srtc.ac.ir/article-1-23-en.pdf}, journal = {Journal of Statistical Research of Iran JSRI}, issn = {2538-5771}, eissn = {2538-5763}, year = {2015} } @article{ author = {AlizadehNoughabi, Hadi}, title = {On the Estimation of Shannon Entropy}, abstract ={Shannon entropy is increasingly used in many applications. In this article, an estimator of the entropy of a continuous random variable is proposed. Consistency and scale invariance of variance and mean squared error of the proposed estimator is proved and then comparisons are made with Vasicek's (1976), van Es (1992), Ebrahimi et al. (1994) and Correa (1995) entropy estimators. A simulation study is performed and the results indicate that the proposed estimator has smaller mean squared error than competing estimators.}, Keywords = {Information theory, entropy estimator, exponential distribution, normal distribution, uniform distribution.}, volume = {12}, Number = {1}, pages = {57-70}, publisher = {Statistical Research and Training Center - Statistical Centre of Iran}, doi = {10.18869/acadpub.jsri.12.1.57}, url = {http://jsri.srtc.ac.ir/article-1-22-en.html}, eprint = {http://jsri.srtc.ac.ir/article-1-22-en.pdf}, journal = {Journal of Statistical Research of Iran JSRI}, issn = {2538-5771}, eissn = {2538-5763}, year = {2015} } @article{ author = {Golshani, Leil}, title = {The Rate of Entropy for Gaussian Processes}, abstract ={In this paper, we show that in order to obtain the Tsallis entropy rate for stochastic processes, we can use the limit of conditional entropy, as it was done for the case of Shannon and Renyi entropy rates. Using that we can obtain Tsallis entropy rate for stationary Gaussian processes. Finally, we derive the relation between Renyi, Shannon and Tsallis entropy rates for stationary Gaussian processes.}, Keywords = {Tsallis entropy, Renyi entropy, Shannon entropy, Gaussian process, entropy rate.}, volume = {12}, Number = {1}, pages = {71-82}, publisher = {Statistical Research and Training Center - Statistical Centre of Iran}, doi = {10.18869/acadpub.jsri.12.1.71}, url = {http://jsri.srtc.ac.ir/article-1-24-en.html}, eprint = {http://jsri.srtc.ac.ir/article-1-24-en.pdf}, journal = {Journal of Statistical Research of Iran JSRI}, issn = {2538-5771}, eissn = {2538-5763}, year = {2015} } @article{ author = {ZamaniMehryan, S. and Sayyareh, A.}, title = {Statistical Inference in Autoregressive Models with Non-negative Residuals}, abstract ={Normal residual is one of the usual assumptions of autoregressive models but in practice sometimes we are faced with non-negative residuals case. In this paper we consider some autoregressive models with non-negative residuals as competing models and we have derived the maximum likelihood estimators of parameters based on the modified approach and EM algorithm for the competing models. Also, based on the simulation study, we have compared the ability of some model selection criteria to select the optimal autoregressive model. Then we consider a set of real data, level of lake Huron 1875-1930, as a data set generated from a first order autoregressive model with non-negative residuals and based on the model selection criteria we select the optimal model between the competing models.}, Keywords = {Autoregressive model, Kullback-Leibler information, model selection criterion, modified maximum likelihood.}, volume = {12}, Number = {1}, pages = {83-104}, publisher = {Statistical Research and Training Center - Statistical Centre of Iran}, doi = {10.18869/acadpub.jsri.12.1.83}, url = {http://jsri.srtc.ac.ir/article-1-27-en.html}, eprint = {http://jsri.srtc.ac.ir/article-1-27-en.pdf}, journal = {Journal of Statistical Research of Iran JSRI}, issn = {2538-5771}, eissn = {2538-5763}, year = {2015} } @article{ author = {Razmkhah, M. and Morabbi, H. and Ahmadi, J.}, title = {Confidence Intervals for Lower Quantiles Based on Two-Sample Scheme}, abstract ={In this paper, a new two-sampling scheme is proposed to construct appropriate confidence intervals for the lower population quantiles. The confidence intervals are determined in the parametric and nonparametric set up and the optimality problem is discussed in each case. Finally, the proposed procedure is illustrated via a real data set. }, Keywords = {Order statistics, coverage probability, optimality, expected width, exponential distribution.}, volume = {12}, Number = {1}, pages = {105-116}, publisher = {Statistical Research and Training Center - Statistical Centre of Iran}, doi = {10.18869/acadpub.jsri.12.1.105}, url = {http://jsri.srtc.ac.ir/article-1-26-en.html}, eprint = {http://jsri.srtc.ac.ir/article-1-26-en.pdf}, journal = {Journal of Statistical Research of Iran JSRI}, issn = {2538-5771}, eissn = {2538-5763}, year = {2015} } @article{ author = {Farnoosh, R. and Hajrajabi, A.}, title = {Skew Normal State Space Modeling of RC Electrical Circuit and Parameters Estimation based on Particle Markov Chain Monte Carlo}, abstract ={Received: 9/21/2013      Approved: 12/9/2015‎ Abstract: In this paper, a skew normal state space model of RC electrical circuit is presented by considering the stochastic differential equation of the this circuit as the dynamic model with colored and white noise and considering a skew normal distribution instead of normal as the measurement noise distribution. Optimal filtering technique via sequential Monte Carlo perspective is developed for tracking the charge as the hidden state of this model. Furthermore, it is assumed that this model contains unknown parameters (resistance, capacitor, mean, variance and shape parameter of the skew normal as the measurement noise distribution). Bayesian framework is applied for estimation of both the hidden charge and the unknown parameters using particle marginal Metropolis-Hastings scheme. It is shown that the coverage percentage of skew normal is more than the one of normal as the measurement noise. Some simulation studies are carried out to demonstrate the efficiency of the proposed approaches.}, Keywords = { RC electrical circuit, state space model, sequential Monte Carlo filtering, parameter estimation.}, volume = {12}, Number = {2}, pages = {129-146}, publisher = {Statistical Research and Training Center - Statistical Centre of Iran}, doi = {10.18869/acadpub.jsri.12.2.129}, url = {http://jsri.srtc.ac.ir/article-1-195-en.html}, eprint = {http://jsri.srtc.ac.ir/article-1-195-en.pdf}, journal = {Journal of Statistical Research of Iran JSRI}, issn = {2538-5771}, eissn = {2538-5763}, year = {2016} } @article{ author = {Kazemi, Reza and Jafari, Ali Akbar}, title = {Modified Signed Log-Likelihood Ratio Test for Comparing the Correlation Coefficients of Two Independent Bivariate Normal Distributions}, abstract ={Received: 11/30/2014             Approved: 5/30/2016‎  Abstract: In this paper, we use the method of modified signed log-likelihood ratio test for the problem of testing the equality of correlation coefficients in two independent bivariate normal distributions. We compare this method with two other approaches, Fisher's Z-transform and generalized test variable, using a Monte Carlo simulation. It indicates that the proposed method is better than the other approaches, in terms of the actual sizes and powers especially when the sample sizes are unequal. We illustrate performance of the proposed approach, using a real data set.}, Keywords = {Bivariate normal distribution, actual size, correlation coefficient, maximum likelihood estimator, power.}, volume = {12}, Number = {2}, pages = {147-162}, publisher = {Statistical Research and Training Center - Statistical Centre of Iran}, doi = {10.18869/acadpub.jsri.12.2.147}, url = {http://jsri.srtc.ac.ir/article-1-192-en.html}, eprint = {http://jsri.srtc.ac.ir/article-1-192-en.pdf}, journal = {Journal of Statistical Research of Iran JSRI}, issn = {2538-5771}, eissn = {2538-5763}, year = {2016} } @article{ author = {Rahnamaei, Z.}, title = {The Location-Scale Mixture of Generalized Gamma Distribution: Estimation and Case Influence Diagnostics}, abstract ={Received: 2/17/2015           Approved: 1/23/2016‎ One of the most interesting problems in distribution theory is constructing the distributions, which are appropriate for fitting skewed and heavy-tailed data sets. In this paper, we introduce a skew-slash distribution by using the scale mixture of the generalized gamma distribution. Some properties of this distribution are obtained. An EM-type algorithm is presented to estimate the parameters. Finally, we provide a simulation study and an application to real data to illustrate the modeling strength of the proposed distribution.}, Keywords = { EM algorithm, generalized gamma distribution, location-scale mixture of distribution, skew-slash distribution.}, volume = {12}, Number = {2}, pages = {163-178}, publisher = {Statistical Research and Training Center - Statistical Centre of Iran}, doi = {10.18869/acadpub.jsri.12.2.163}, url = {http://jsri.srtc.ac.ir/article-1-194-en.html}, eprint = {http://jsri.srtc.ac.ir/article-1-194-en.pdf}, journal = {Journal of Statistical Research of Iran JSRI}, issn = {2538-5771}, eissn = {2538-5763}, year = {2016} } @article{ author = {Ghafouri, S. and HabibiRad, A. and Doostparast, M.}, title = {Bayesian Two-sample Prediction with Progressively Censored Data for Generalized Exponential Distribution Under Symmetric and Asymmetric Loss Functions}, abstract ={Received: 4/12/2015            Approved: 2/6/2016‎ Statistical prediction analysis plays an important role in a wide range of fields. Examples include engineering systems, design of experiments, etc. In this paper, based on progressively Type-II right censored data, Bayesian two-sample point and interval predictors are developed under both informative and non-informative priors. By assuming a generalized exponential model, prediction bounds as well as Bayes point predictors are obtained under the squared error loss (SEL) and the Linear-Exponential (LINEX) loss functions for the order statistic in a future progressively Type-II censored sample with an arbitrary progressive censoring scheme. The derived results may be used for prediction of total time on test in lifetime experiments. %in reliability analyses In addition to numerical method, Gibbs sampling procedure (as Markov Chain Monte Carlo method) are used to assess approximate prediction bounds and Bayes point predictors under the SEL and LINEX loss functions. The performance of the proposed prediction procedures are also demonstrated via a Monte Carlo simulation study and an illustrative example, for each method.}, Keywords = { Bayesian prediction, generalized exponential model, gibbs sampling, LINEX loss function, Markov Chain Monte Carlo, progressive type-II censoring scheme, two-sample prediction.}, volume = {12}, Number = {2}, pages = {179-204}, publisher = {Statistical Research and Training Center - Statistical Centre of Iran}, doi = {10.18869/acadpub.jsri.12.2.179}, url = {http://jsri.srtc.ac.ir/article-1-193-en.html}, eprint = {http://jsri.srtc.ac.ir/article-1-193-en.pdf}, journal = {Journal of Statistical Research of Iran JSRI}, issn = {2538-5771}, eissn = {2538-5763}, year = {2016} } @article{ author = {Nekoukhou, Vahi}, title = {The Beta-Rayleigh Distribution on the Lattice of Integers}, abstract ={Received: 9/14/2015      Approved: 5/28/2016‎ In this paper, a discrete analog of the beta-Rayleigh distribution is studied. This new distribution contains the generalized discrete Rayleigh and discrete Rayleigh distributions as special sub-models. Some distributional and moment properties of the new discrete distribution as well as its order statistics are discussed. We will see that the hazard rate function of the new model can be increasing, bathtub-shaped and upside-down bathtub. Estimation of the parameters is illustrated and, finally, the model with a real data set is examined.}, Keywords = { Discrete Rayleigh distribution, generalized discrete Rayleigh distribution, exponentiated discrete Weibull distribution, hazard rate function.}, volume = {12}, Number = {2}, pages = {205-224}, publisher = {Statistical Research and Training Center - Statistical Centre of Iran}, doi = {10.18869/acadpub.jsri.12.2.205}, url = {http://jsri.srtc.ac.ir/article-1-197-en.html}, eprint = {http://jsri.srtc.ac.ir/article-1-197-en.pdf}, journal = {Journal of Statistical Research of Iran JSRI}, issn = {2538-5771}, eissn = {2538-5763}, year = {2016} } @article{ author = {NaghizadehQomi, M. and Barmoodeh, L.}, title = {Shrinkage Testimation in Exponential Distribution based on Records under Asymmetric Squared Log Error Loss}, abstract ={Received: 1/9/2016                Approved: 6/1/2016‎  In the present paper, we study shrinkage testimation for the unknown scale parameter $theta>0$ of the exponential distribution based on record data under the asymmetric squared log error loss function. A minimum risk unbiased estimator within the class of the estimators of the form $cT_m$ is derived, where $T_m$ is the maximum likelihood estimate of $theta$. Some shrinkage testimators are proposed and their risks are computed. The relative efficiencies of the shrinkage testimators with respect to a minimum risk unbiased estimator of the form $cT_m$ under the squared log error loss function are calculated for the comparison purposes. An illustrative example is also presented.}, Keywords = {Digamma function, exponential distribution, records, shrinkage testimators.}, volume = {12}, Number = {2}, pages = {225-238}, publisher = {Statistical Research and Training Center - Statistical Centre of Iran}, doi = {10.18869/acadpub.jsri.12.2.225}, url = {http://jsri.srtc.ac.ir/article-1-196-en.html}, eprint = {http://jsri.srtc.ac.ir/article-1-196-en.pdf}, journal = {Journal of Statistical Research of Iran JSRI}, issn = {2538-5771}, eissn = {2538-5763}, year = {2016} }