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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Communications for Statistical Applications and Methods
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Journal DOI :
The Korean Statistical Society
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Volume & Issues
Volume 20, Issue 6 - Nov 2013
Volume 20, Issue 5 - Sep 2013
Volume 20, Issue 4 - Jul 2013
Volume 20, Issue 3 - May 2013
Volume 20, Issue 2 - Mar 2013
Volume 20, Issue 1 - Jan 2013
Selecting the target year
Approximate Confidence Limits for the Ratio of Two Binomial Variates with Unequal Sample Sizes
Cho, Hokwon ;
Communications for Statistical Applications and Methods, volume 20, issue 5, 2013, Pages 347~356
DOI : 10.5351/CSAM.2013.20.5.347
We propose a sequential method to construct approximate confidence limits for the ratio of two independent sequences of binomial variates with unequal sample sizes. Due to the nonexistence of an unbiased estimator for the ratio, we develop the procedure based on a modified maximum likelihood estimator (MLE). We generalize the results of Cho and Govindarajulu (2008) by defining the sample-ratio when sample sizes are not equal. In addition, we investigate the large-sample properties of the proposed estimator and its finite sample behavior through numerical studies, and we make comparisons from the sample information view points.
Improved Exponential Estimator for Estimating the Population Mean in the Presence of Non-Response
Kumar, Sunil ;
Communications for Statistical Applications and Methods, volume 20, issue 5, 2013, Pages 357~366
DOI : 10.5351/CSAM.2013.20.5.357
This paper defines an improvement for estimating the population mean of a study variable using auxiliary information and known values of certain population parameter(s), when there is a non-response in a study as well as on auxiliary variables. Under a simple random sampling without a replacement (SRSWOR) scheme, the mean square error (MSE) of all proposed estimators are obtained and compared with each other. Numerical illustration is also given.
An Improved Composite Estimator for Cut-off Sampling
Hwang, Hee-Jin ; Shin, Key-Il ;
Communications for Statistical Applications and Methods, volume 20, issue 5, 2013, Pages 367~376
DOI : 10.5351/CSAM.2013.20.5.367
Cut-off sampling is widely used for a highly skewed population like a business survey by discarding a part of the population (the take-nothing stratum). In this paper, we suggest a new composite estimator of the take-nothing stratum total obtained by use of the survey results of the take-nothing stratum and a take-some sub-stratum (a part of take-some stratum) for a more accurate estimate of the population total. Small simulation studies are conducted to compare the performances of known estimators and the new composite estimator suggested in this study. In addition, we use briquette consumption survey data for real data analysis.
A Compound Poisson Risk Model with a Two-Step Premium Rule
Song, Mi Jung ; Lee, Jiyeon ;
Communications for Statistical Applications and Methods, volume 20, issue 5, 2013, Pages 377~385
DOI : 10.5351/CSAM.2013.20.5.377
We consider a compound Poisson risk model in which the premium rate changes when the surplus exceeds a threshold. The explicit form of the ruin probability for the risk model is obtained by deriving and using the overflow probability of the workload process in the corresponding M/G/1 queueing model.
Noninformative Priors for the Ratio of the Scale Parameters in the Inverted Exponential Distributions
Kang, Sang Gil ; Kim, Dal Ho ; Lee, Woo Dong ;
Communications for Statistical Applications and Methods, volume 20, issue 5, 2013, Pages 387~394
DOI : 10.5351/CSAM.2013.20.5.387
In this paper, we develop the noninformative priors for the ratio of the scale parameters in the inverted exponential distributions. The first and second order matching priors, the reference prior and Jeffreys prior are developed. It turns out that the second order matching prior matches the alternative coverage probabilities, is a cumulative distribution function matching prior and is a highest posterior density matching prior. In addition, the reference prior and Jeffreys' prior are the second order matching prior. We show that the proposed reference prior matches the target coverage probabilities in a frequentist sense through a simulation study as well as provide an example based on real data is given.
Skewness of Gaussian Mixture Absolute Value GARCH(1, 1) Model
Lee, Taewook ;
Communications for Statistical Applications and Methods, volume 20, issue 5, 2013, Pages 395~404
DOI : 10.5351/CSAM.2013.20.5.395
This paper studies the skewness of the absolute value GARCH(1, 1) models with Gaussian mixture innovations (Gaussian mixture AVGARCH(1, 1) models). The maximum estimated-likelihood estimator (MELE) employed (a two- step estimation method in order to estimate the skewness of Gaussian mixture AVGARCH(1, 1) models. Through the real data analysis, the adequacy of adopting Gaussian mixture innovations is exhibited in reflecting the skewness of two major Korean stock indices.
An Analysis of Record Statistics based on an Exponentiated Gumbel Model
Kang, Suk Bok ; Seo, Jung In ; Kim, Yongku ;
Communications for Statistical Applications and Methods, volume 20, issue 5, 2013, Pages 405~416
DOI : 10.5351/CSAM.2013.20.5.405
This paper develops a maximum profile likelihood estimator of unknown parameters of the exponentiated Gumbel distribution based on upper record values. We propose an approximate maximum profile likelihood estimator for a scale parameter. In addition, we derive Bayes estimators of unknown parameters of the exponentiated Gumbel distribution using Lindley's approximation under symmetric and asymmetric loss functions. We assess the validity of the proposed method by using real data and compare these estimators based on estimated risk through a Monte Carlo simulation.
On Estimating the Parameters of an Extended Form of Logarithmic Series Distribution
Kumar, C. Satheesh ; Riyaza, A. ;
Communications for Statistical Applications and Methods, volume 20, issue 5, 2013, Pages 417~425
DOI : 10.5351/CSAM.2013.20.5.417
We consider an extended version of a logarithmic series distribution and discuss the estimation of its parameters by the method of moments and the method of maximum likelihood. Test procedures are suggested to test the significance of the additional parameter of this distribution and all procedures are illustrated with the help of real life data sets. In addition, a simulation study is conducted to assess the performance of the estimators.