• Korean journal of applied entomology
• /
• v.55 no.4
• /
• pp.405-412
• /
• 2016

Infestation of adults and pupae of sweetpotato whitefly, Bemisia tabaci, on paprika (Capsicum annuum var. angulosum) grown in greenhouses in Jinju, Gyeongnam province during 2014was determined by counts of the number of target stage of B. tabaci per leaflet. Binomial sampling plans were developed based on the relationship between the mean density per leaflet (m) and the proportion of leaflets infested with less than T whiteflies ($P_T$), according to the empirical model $(({\ln}(m)={\alpha}+{\beta}({\ln}(-{\ln}(1-P_T))))$. T was defined as the tally threshold, and set to 1, 2, 3, 4, 5 (adults) and 1, 3, 5, 7 (pupae) per leaflet in this study. Increasing the sample size, regardless of tally threshold, had little effect on the precision of the binomial sampling plan. Based on the precision of the model, T = 1 was chosen as the best tally threshold for estimating densities of B. tabaci adults and T = 3 was best tally threshold in B. tabaci pupae. Using the results obtained in the greenhouse, a simulated validation of the developed sampling plan by RVSP (Resampling Validation for Sampling Plan) demonstrated the plan's validity. Above all, the binomial model with T = 1 and T = 3 provided reliable predictions of the mean densities of B. tabaci adults and pupae on greenhouse paprika.

• Journal of the Korean Data and Information Science Society
• /
• v.12 no.1
• /
• pp.1-9
• /
• 2001

In this paper, the problem of information related to I binomial experiments, each having a distinct probability of success ${\theta}_i$, i = 1,2, $\cdots$, I, is considered. Instead of using a standard exchangeable prior for ${\theta}\;=\;({\theta}_1,\;{\theta}_2,\;{\cdots},\;{\theta}_I)$, we con-sider a partition of the experiments and take the ${\theta}_i$'s belonging to the same partition subset to be exchangeable and the ${\theta}_i$'s belonging to distinct subsets to be independent. And we perform Gibbs sampler approach for Bayesian inference on $\theta$ conditional on a partition. Also we illustrate the methodology with a real data.

• Journal of the Korean Statistical Society
• /
• v.31 no.1
• /
• pp.45-61
• /
• 2002

We consider the problem of estimating binomial proportions in the presence of nonignorable nonresponse using the Bayesian selection approach. Inference is sampling based and Markov chain Monte Carlo (MCMC) methods are used to perform the computations. We apply our method to study doctor visits data from the Korean National Family Income and Expenditure Survey (NFIES). The ignorable and nonignorable models are compared to Stasny's method (1991) by measuring the variability from the Metropolis-Hastings (MH) sampler. The results show that both models work very well.

• Communications for Statistical Applications and Methods
• /
• v.16 no.3
• /
• pp.501-509
• /
• 2009

Recently the interval estimation of binomial proportions is revisited in various literatures. This is mainly due to the erratic behavior of the coverage probability of the well-known Wald confidence interval. Various alternatives have been proposed. Among them, the Agresti-Coull confidence interval, the Wilson confidence interval and the Bayes confidence interval resulting from the noninformative Jefferys prior were recommended by Brown et al. (2001). However, unlike the binomial distribution case, little is known about the properties of the confidence intervals in finite population sampling. In this note, the property of confidence intervals is investigated in anile population sampling.

• Honam Mathematical Journal
• /
• v.5 no.1
• /
• pp.251-260
• /
• 1983

• Korean journal of applied entomology
• /
• v.37 no.2
• /
• pp.151-157
• /
• 1998

Infestations of two spotted spider mite (TSSM), Tetranychus urticae Koch, on glasshouse rose (Rosa sp.) grown by an arching method, were determined by counts of the number of TSSM per leaflet in Buyeo, Chungnam Province, for a 2-yr period. Binomial sampling plans were developed based on the relationship between mean density per leaflet (m), and proportion of leaflets infested with ( T mites (PT), according to the empirical model In (m) = a+p In (-ln (1 -PT)). T was defined as tally threshold, and set to 1, 3, 5, 7, and 9 mites per leaflet. Increasing sample size had little effects on the precision of the binomial sampling plan, regardless of tally threshold. However, the precision increased with higher tally thresholds. There was a negligible improvement in precision with T ) 7 mites per leaflet. T= 7 was chosen as the best tally threshold for estimating densities of TSSM based on the precision of the model. Independent data set was used to evaluate the model. The binomial model with T= 7 provided reliable predictions of mean densities of TSSM observed on the commercial glasshouse roses.

• Communications for Statistical Applications and Methods
• /
• v.17 no.3
• /
• pp.309-318
• /
• 2010

The construction of asymptotic confidence intervals is considered for the difference of binomial proportions in two doubly sampled data subject to false-positive error. The coverage behaviors of several likelihood based confidence intervals and a Bayesian confidence interval are examined. It is shown that a hierarchical Bayesian approach gives a confidence interval with good frequentist properties. Confidence interval based on the Rao score is also shown to have good performance in terms of coverage probability. However, the Wald confidence interval covers true value less often than nominal level.

• Journal of applied mathematics & informatics
• /
• v.42 no.1
• /
• pp.179-187
• /
• 2024

In the Quality Control and inspection processes, the use of attribute sampling strategies is crucial. In this study, we incorporate the neutrosophic fuzzy acceptance sampling plan method to present a fresh approach to attribute sampling plans. Utilizing the benefits of neutrosophic fuzzy sets, the proposed sampling plan method models and assesses the acceptance standards for attribute sampling. We compare the suggested method to already-in-use attribute sampling techniques plans with new attribute six sigma sampling techniques plan is proposed in order to verified its efficacy. The outcomes show the neutrosophic fuzzy acceptance sampling plan's superiority in terms of its capacity to manage uncertainties, account for ambiguity, and produce more precise quality evaluation outputs.

• Journal of Korean Society for Quality Management
• /
• v.30 no.2
• /
• pp.152-159
• /
• 2002

An acceptance sampling plan for products manufactured from a production process with variable fraction defective is developed. We consider a situation where defective products have short lifetimes and non-defective ones never fail during the technological life of the products. An acceptance criterion which guarantee the out going quality of accepted products is derived using the prior information on the quality of products. Numerical examples are provided.

• Journal of the Korean Data and Information Science Society
• /
• v.10 no.1
• /
• pp.199-205
• /
• 1999

This paper discusses the generalized mixed-effects model for the analysis of overdispersed binomial data. Sometimes certain types of sampling designs or genetic characters of experimental units can be regarded as factors of extra binomial variation. For such cases, this paper suggests models with one or two random effects to explain overdispersion caused by those affecting factors and shows how to test for a model adequacy based on deviance.