• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1419-1427
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• 2008

This paper shows the kernel Poisson regression which can be applied in the claims reserving, where the row effect is assumed to be a nonlinear function of the row index. The paper concentrates on the chain-ladder technique, within the framework of the chain-ladder linear model. It is shown that the proposed method can provide better reserve estimates than the Poisson model. The cross validation function is introduced to choose optimal hyper-parameters in the procedure. Experimental results are then presented which indicate the performance of the proposed model.

• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1353-1360
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• 2008

An estimating procedure is introduced for the nonlinear mixed-effect Poisson regression, for longitudinal study, where data from different subjects are independent whereas data from same subject are correlated. The proposed procedure provides the estimates of the mean function of the response variables, where the canonical parameter is related to the input vector in a nonlinear form. The generalized cross validation function is introduced to choose optimal hyper-parameters in the procedure. Experimental results are then presented, which indicate the performance of the proposed estimating procedure.

• Bulletin of the Korean Chemical Society
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• v.31 no.9
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• pp.2553-2556
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• 2010

On the basis of a simple modified Poisson-Boltzmann (SMPB) theory, taking into account the finite ionic size, the analytic expression for the effect of ionic size on the diffuse layer potential drop at negative charge densities has been given for the simple 1:1 electrolyte. It is shown that the potential drop across the diffuse layer depends on the size of the ions in the electrolyte. For a given electrolyte concentration and electrode charge density, the diffuse layer potential drop in a small ion system is smaller than that in a large ion system. It is also displayed that the diffuse layer potential drop is always less than the value of the Gouy-Chapman (GC) theory, and the deviation increases as the electrode charge density increases for a given electrolyte concentration. These theoretical results are consistent with the results of the Monte-Carlo simulation [Fawcett and Smagala, Electrochimica Acta 53, 5136 (2008)], which indicates the importance of including steric effects in modeling diffuse layer properties.

• Advances in nano research
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• v.10 no.5
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• pp.423-435
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• 2021

This paper examines the thermal post-buckling behaviors of graphene-reinforced metal matrix composite (GRMMC) laminated cylindrical panels which possess in-plane negative Poisson's ratio (NPR) and rest on an elastic foundation. A panel consists of GRMMC layers of piece-wise varying graphene volume fractions to obtain functionally graded (FG) patterns. Based on the MD simulation results, the GRMMCs exhibit in-plane NPR as well as temperature-dependent material properties. The governing equations for the thermal post-buckling of panels are based on the Reddy's third order shear deformation shell theory. The von Karman nonlinear strain-displacement relationship and the elastic foundation are also included. The nonlinear partial differential equations for GRMMC laminated cylindrical panels are solved by means of a singular perturbation technique in associate with a two-step perturbation approach and in the solution process the boundary layer effect is considered. The results of numerical investigations reveal that the thermal post-buckling strength for (0/90)_5T GRMMC laminated cylindrical panels can be enhanced with an FG-X pattern. The thermal post-buckling load-deflection curve of 6-layer (0/90/0)_S and (0/90)_3T panels of FG-X pattern are higher than those of 10-layer (0/90/0/90/0)_S and (0/90)_5T panels of FG-X pattern.

• The Korean Journal of Applied Statistics
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• v.27 no.3
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• pp.445-459
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• 2014

As a certain job is repeatedly done by a worker, the outcome comparative to the effort to complete the job gets more remarkable. The outcome may be the time required and fraction defective. This phenomenon is referred to a learning-curve effect. We focus on the parametric modeling of the learning-curve effects on count data using a logistic cumulative distribution function and some probability mass functions such as a Poisson and negative binomial. We conduct various simulation scenarios to clarify the characteristics of the proposed model. We also consider a real application to compare the two discrete-type distribution functions.

• Journal of Powder Materials
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• v.25 no.6
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• pp.507-513
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• 2018

This study investigates the viability of using a Na-ion battery with a tin(Sn) anode to mitigate the vulnerability caused by volume changes during discharge and charge cycling. In general, the volume changes of carbon material do not cause any instability during intercalation into its layer structure. Sn has a high theoretical capacity of $847mAh\;g^{-1}$. However, it expands dramatically in the discharge process by alloying Na-Sn, placing the electrode under massive internal stress, and particularly straining the binder over the elastic limit. The repeating strain results in loss of active material and its electric contact, as well as capacity decrease. This paper expands the scope of fabrication of Na-ion batteries with Sn by fabricating the binder as an auxetic structure with a unique feature: a negative Poisson ratio (NPR), which increases the resistance to internal stress in the Na-Sn alloying/de-alloying processes. Electrochemical tests and micrograph images of auxetic and common binders are used to compare dimensional and structural differences. Results show that the capacity of an auxetic-structured Sn electrode is much larger than that of a Sn electrode with a common-structured binder. Furthermore, using an auxetic structured Sn electrode, stability in discharge and charge cycling is obtained.

• Journal of Korean Society of Transportation
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• v.21 no.3
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• pp.15-22
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• 2003

In general, the linear regression model has been used to estimate trip generation in the travel demand forecasting procedure. However, the model suffers from several methodological limitations. First, trips as a dependent variable with non-negative integer show discrete distribution but the model assumes that the dependent variable is continuously distributed between -$\infty$ and +$\infty$. Second, the model may produce negative estimates. Third, even if estimated trips are within the valid range, the model offers only forecasted trips without discrete probability distribution of them. To overcome these limitations, a poisson model with a assumption of equidispersion has frequently been used to analyze count data such as trip frequencies. However, if the variance of data is greater than the mean. the poisson model tends to underestimate errors, resulting in unreliable estimates. Using overdispersion test, this study proved that the poisson model is not appropriate and by using Vuong test, zero inflated negative binomial model is optimal. Model reliability was checked by likelihood test and the accuracy of model by Theil inequality coefficient as well. Finally, marginal effect of the change of socio-demographic characteristics of households on trips was analyzed.

• The Journal of Economics, Marketing and Management
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• v.9 no.2
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• pp.33-43
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• 2021

Purpose: This study aims to verify sellers' economic incentives for voluntarily disclosing negative information in online markets and provide practical guidelines to online sellers in terms of whether, when, and how sharing low quality to buyers increase sales. Research design, data and methodology: Our model examines the number of bidders in Internet auctions to measure potential demand and uses count data analysis following previous studies that have also analyzed the number of bidders in auctions. After checking over-dispersion and zero-inflation in our data, we have run a Poisson regression to analyze the effect of sharing negative information on sales. Results: This study presents a counterintuitive result that low-quality sellers can increase their demand by fully disclosing negative information in an online market, if appropriate risk-reducing methods are employed. Our finding thus shows that there exists economic incentive for online sellers to voluntarily disclose negative information about their products, and that the context of transactions may affect this incentive structure as the incentive varies across product categories. Conclusions: As the positive impact of disclosing negative information has rarely been studied so far, this paper contributes to the literature by providing a unique empirical analysis on the impact of sellers' honesty on sales. By verifying economic incentives of disclosing low quality with actual online sales data, this study suggests practical implications on information disclosure strategy to many online sellers dealing with negative information.

• Environmental and Resource Economics Review
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• v.27 no.3
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• pp.545-567
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• 2018

This study applied and compared Poisson model, negative binomial model, zero inflated Poisson model, and zero inflated negative binomial model to estimate determinants of employed labour quantity. To estimate each of models, this study used fisheries census data which were obtained at microdata integrated service running by Statistics Korea. The study selected zero inflated negative binomial model according to the Vuong test and Likelihood-ratio test. In addition, the study estimated fishing village's practical changes on employed labour quantity as analyzing changes from 2010 to 2015. The results showed that the household with fishing vessels and high selling price had a significant effect on decrease of the labour quantities. Meanwhile, the longer work experience of the household, the more significant the increase in the labour quantities. In conclusion, this study presented that capitalized fishing household and the acceleration of aging had a significant impact on the change in the labour quantities.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.43-61
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• 2016

Customer reviews help potential customers make purchasing decisions. However, the prevalence of reviews on websites push the customer to sift through them and change the focus from a mere search to identifying which of the available reviews are valuable and useful for the purchasing decision at hand. To identify useful reviews, websites have developed different mechanisms to give customers options when evaluating existing reviews. Websites allow users to rate the usefulness of a customer review as helpful or not. Amazon.com uses a ratio-type helpfulness, while Yelp.com uses a count-type usefulness index. This usefulness index provides helpful reviews to future potential purchasers. This study investigated the effects of sentiment and readability on useful votes for customer reviews. Similar studies on the relationship between sentiment and readability have focused on the ratio-type usefulness index utilized by websites such as Amazon.com. In this study, Yelp.com's count-type usefulness index for restaurant reviews was used to investigate the relationship between sentiment/readability and usefulness votes. Yelp.com's online customer reviews for stores in the beverage and food categories were used for the analysis. In total, 170,294 reviews containing information on a store's reputation and popularity were used. The control variables were the review length, store reputation, and popularity; the independent variables were the sentiment and readability, while the dependent variable was the number of helpful votes. The review rating is the moderating variable for the review sentiment and readability. The length is the number of characters in a review. The popularity is the number of reviews for a store, and the reputation is the general average rating of all reviews for a store. The readability of a review was calculated with the Coleman-Liau index. The sentiment is a positivity score for the review as calculated by SentiWordNet. The review rating is a preference score selected from 1 to 5 (stars) by the review author. The dependent variable (i.e., usefulness votes) used in this study is a count variable. Therefore, the Poisson regression model, which is commonly used to account for the discrete and nonnegative nature of count data, was applied in the analyses. The increase in helpful votes was assumed to follow a Poisson distribution. Because the Poisson model assumes an equal mean and variance and the data were over-dispersed, a negative binomial distribution model that allows for over-dispersion of the count variable was used for the estimation. Zero-inflated negative binomial regression was used to model count variables with excessive zeros and over-dispersed count outcome variables. With this model, the excess zeros were assumed to be generated through a separate process from the count values and therefore should be modeled as independently as possible. The results showed that positive sentiment had a negative effect on gaining useful votes for positive reviews but no significant effect on negative reviews. Poor readability had a negative effect on gaining useful votes and was not moderated by the review star ratings. These findings yield considerable managerial implications. The results are helpful for online websites when analyzing their review guidelines and identifying useful reviews for their business. Based on this study, positive reviews are not necessarily helpful; therefore, restaurants should consider which type of positive review is helpful for their business. Second, this study is beneficial for businesses and website designers in creating review mechanisms to know which type of reviews to highlight on their websites and which type of reviews can be beneficial to the business. Moreover, this study highlights the review systems employed by websites to allow their customers to post rating reviews.