• The Korean Journal of Applied Statistics
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• v.35 no.2
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• pp.311-325
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• 2022

For count responses, the situation of excess zeros often occurs in various research fields. Zero-inflated model is a common choice for modeling such count data. Bayesian inference for the zero-inflated model has long been recognized as a hard problem because the form of conditional posterior distribution is not in closed form. Recently, however, Pillow and Scott (2012) and Polson et al. (2013) proposed a Pólya-Gamma data-augmentation strategy for logistic and negative binomial models, facilitating Bayesian inference for the zero-inflated model. We apply Bayesian zero-inflated negative binomial regression model to longitudinal pharmaceutical data which have been previously analyzed by Min and Agresti (2005). To facilitate posterior sampling for longitudinal zero-inflated model, we use the Pólya-Gamma data-augmentation strategy.

• Journal of the Korean Statistical Society
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• v.29 no.4
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• pp.435-441
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• 2000

Ko(1998, 1999) proposed certain flexible two-stage plans that could be served as one-step interim analysis in on-going clinical trials. The proposed Plans are optimal simultaneously in both a Bayes and a Neyman-Pearson sense. The Neyman-Pearson interpretation is that average expected sample size is being minimized, subject just to the two overall error rates $\alpha$ and $\beta$, respectively of first and second kind. The Bayes interpretation is that Bayes risk, involving both sampling cost and wrong decision losses, is being minimized. An example of this correspondence are given by using a binomial setting.

• Proceedings of the Korean Statistical Society Conference
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• 2003.10a
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• pp.253-256
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• 2003

In ecological studies, animal science, or entomology, the variance of count is considered to have the power of the mean relationship with the mean count as Taylor (1961) presented his famous 'Taylor's Power Law'. In this talk, we are going to review the development of TPL and its extension toward pest management sampling scheme. Different estimation methods are compared. Quasilikelihood approach is suggested to incorporate covariate information. Possible extensions will be discussed.

• The Korean Journal of Applied Statistics
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• v.25 no.3
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• pp.513-520
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• 2012

An Agresti-Coull type test is considered for the difference of binomial proportions in two doubly sampled data subject to false-positive error. The performance of the test is compared with the likelihood-based tests. It is shown that the Agresti-Coull test has many desirable properties in that it can approximate the nominal significance level with compatible power performance.

• The Korean Journal of Applied Statistics
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• v.25 no.4
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• pp.697-706
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• 2012

An Agresti-Coull type test is considered for the difference of binomial proportions in two doubly sampled data subject to common false-positive error. The performance of the test is compared with likelihood-based tests. The Agresti-Coull test has many desirable properties in that it can approximate the nominal significance level well, and has comparable power performance with a computational advantage.

• Communications for Statistical Applications and Methods
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• v.17 no.5
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• pp.679-688
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• 2010

Lee (2010) developed a confidence interval for the difference of binomial proportions in two doubly sampled data subject to false-positive errors. The confidence interval seems to be adequate for a general double sampling model subject to false-positive misclassification. However, in many applications, the false-positive error rates could be the same. On this note, the construction of asymptotic confidence interval is considered when the false-positive error rates are common. The coverage behaviors of nine likelihood based confidence intervals are examined. It is shown that the confidence interval based Rao score with the expected information has good performance in terms of coverage probability and expected width.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.523-532
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• 1999

Generalized linear models have various applications for data arising from many kinds of statistical studies. Although the response variable is generally assumed to be generated from a wide class of probability distributions we focus on count data that are most often analyzed using binomial models for proportions or poisson models for rates. The methods and results presented here also apply to many other categorical data models in general due to the relationship between multinomial and poisson sampling. The novelty of the approach suggested here is that all conditional distribution s can be specified directly so that staraightforward Gibbs sampling is possible. The prior distribution consists of two stages. We rely on a normal nonconjugate prior at the first stage and a vague prior for hyperparameters at the second stage. The methods are demonstrated with an illustrative example using data collected by Rosenkranz and raftery(1994) concerning the number of hospital admissions due to back pain in Washington state.

• Korean journal of applied entomology
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• v.51 no.2
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• pp.91-97
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• 2012

The dispersion indices, spatial pattern and sampling plan for pink citrus rust mite (PCRM), Aculops pelekassi, monitoring was investigated. Dispersion indices of PCRM indicated the aggregated spatial pattern. Taylor's power law provided better description of variance-mean relationship than Iwao's patchiness regression. Fixed-precision levels (D) of a sequential sampling plan were developed using by Taylor's power law parameters generated from PCRM on fruit sample (cumulated number of PCRM in $cm^2$ of fruit). Based on Kono-Sugino's empirical binomial the mean density per $cm^2$ could be estimated from fruit ratio with more than 12 rust mites per $cm^2$: $ln(m)=4.61+1.23ln[-ln(1-p_{12})]$. To determine the optimal tally threshold, the variance (var(lnm)) for mean (lnm) in Kono-Sugino equation was estimated. The lower and narrow ranged change of variance for esimated mean showed at a tally threshold of 12. To estimate PCRM mean density per $cm^2$ at fixed precision level 0.25, the required sample number was 13 trees, 5 fruits per tree and 2 points per fruit (total 130 samples).

• Korean journal of applied entomology
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• v.48 no.1
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• pp.45-51
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• 2009

This paper presents sequential sampling plans for evaluating the pest density based on complete counts from probe in a rice storage warehouse. Both maize weevil and Indian meal moth population showed negative binomial dispersion patterns in brown rice storage. For cost-effective monitoring and action decision making system, sequential sampling plans by using the sequential probability ratio test (SPRT) were developed for the maize weevil and Indian meal moth in warehouses with 0.8 M/T storage bags. The action threshold for the two insect pests was estimated to 5 insects per kg, which was projected by a matrix model. The results show that, using SPRT methods, managers can make decisions using only 20 probe with a minimum risk of incorrect assessment.

• Management & Information Systems Review
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• v.33 no.2
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• pp.301-315
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• 2014

The purpose of this study is to estimate the economic value of the Kumjung Mountain, using a Individual Travel Cost Model(ITCM). This paper compares Poisson and negative binomial count data models to measure the tourism demands. Interviewers were instructed to interview only individuals. So the sample was taken in 700. A dependent variable that is defined on the non-negative integers and subject to sampling truncation is the result of a truncated count data process. The results suggest that the truncated negative binomial model is improved overdispersion problem and more preferred than the other models in the study. This study emphasizes in particular 'travel cost' that is not only monetary cost but also including opportunity cost of 'travel time'. According to the truncated negative binomial model, estimates the Consumer Surplus(CS) values per trip of about 60,669 Korean won and the total economic value was estimated to be 252,383 Korean won.