• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.535-543
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• 2020

Investors from the whole world are looking for those stock markets that are less affected by interest rates. Pakistan is a good place to invest and the investors from the whole world are considering Pakistan for future ventures. The current study, therefore, aims to analyze the factors affecting investors' decision making in Pakistan with the interaction effect of locus of control. The primary data are gathered from 300 respondents. Structural equation modelling (SEM-PLS) is used to analyze the interactions among variables. The study finds positive impact of availability and representative biases on investment decision making. The study could not find any moderating role of locus of control. The results imply that decisions made by Pakistani investors are driven by the most easily or currently available information and they trust on the information obtained from family and friends without any authentication and verification. One possible description of insignificant moderation effect of locus of control can be the sample traits used in the study, e.g., personal characteristics, that change from culture to culture. Another description of these findings may be the association between heuristic biases, including availability, representative and psychological biases and decision-making regarding investment is not personality specific.

• Journal of Fashion Business
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• v.11 no.1
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• pp.26-37
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• 2007

Madeleine Vionnet(1876$\sim$1975, France),the most prominent figure of the 20th century draping, started her apprentice in France in 1888 and expressed feminity of adult products through her various works until she closed the house in 1940. The feminine designs of the adult style appeared in 1930s, whose characteristics were silhouette and details that emphasize the body, and bias designs. Not only Vionnet, but also Chanel and Schiaparelli were the representative female designers at that time. The preliminary researches of Vionnet designs were mostly focused on her cutting methods. This paper purports to examine Vionnet's bias cutting method, to compare Vionnet with female designers of Chanel and Schiaparelli who led the mode of 1930s with feminine designs for the adult products in that period, and then to attempt creative designs by use of bias cutting.

• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.1127-1135
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• 2014

Genome-wide association studies (GWAS) are designed to discover genetic variants such as single nucleotide polymorphisms (SNPs) that are associated with human complex traits. Although there is an increasing interest in the application of GWAS methodologies to population-based cohorts, many published GWAS have adopted a case-control design, which raise an issue related to a sampling bias of both case and control samples. Because of unequal selection probabilities between cases and controls, the samples are not representative of the population that they are purported to represent. Therefore, non-random sampling in case-control study can potentially lead to inconsistent and biased estimates of SNP-trait associations. In this paper, we proposed inverse-probability of sampling weights based on disease prevalence to eliminate a case-control sampling bias in estimation and testing for association between SNPs and quantitative traits. We apply the proposed method to a data from the Korea Association Resource project and show that the standard estimators applied to the weighted data yield unbiased estimates.

• Journal of Korea Water Resources Association
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• v.52 no.5
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• pp.337-347
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• 2019

This study proposes the framework to select the representative general circulation model (GCM) for climate change projection. The grid-based results of GCMs were transformed to all considered meteorological stations using inverse distance weighted (IDW) method and its results were compared to the observed precipitation. Six quantile mapping methods and random forest method were used to correct the bias between GCM's and the observation data. Thus, the empirical quantile which belongs to non-parameteric transformation method was selected as a best bias correction method by comparing the measures of performance indicators. Then, one of the multi-criteria decision techniques, TOPSIS (Technique for Order of Preference by Ideal Solution), was used to find the representative GCM using the performances of four GCMs after the bias correction using empirical quantile method. As a result, GISS-E2-R was the best and followed by MIROC5, CSIRO-Mk3-6-0, and CCSM4. Because these results are limited several GCMs, different results will be expected if more GCM data considered.

• Journal of Biomedical Engineering Research
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• v.19 no.2
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• pp.133-142
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• 1998

In Bayesian SPECT reconstruction, the incorporation of elaborate forms of priors can lead to improved quantitative performance in various statistical terms, such as bias and variance. In particular, the use of higher-order smoothing priors, such as the thin-plate prior, is known to exhibit improved bias behavior compared to the conventional smoothing priors such as the membrane prior. However, the bias advantage of the higher-order priors is effective only when the hyperparameters involved in the reconstruction algorithm are properly chosen. In this work, we further investigate the quantitative performance of the two representative smoothing priors-the thin plate and the membrane-by observing the behavior of the associated hyperparameters of the prior distributions. In our experiments we use Monte Carlo noise trials to calculate bias and variance of reconstruction estimates, and compare the performance of ML-EM estimates to that of regularized EM using both membrane and thin-plate priors, and also to that of filtered backprojection, where the membrane and thin plate models become simple apodizing filters of specified form. We finally show that the use of higher-order models yields excellent "robustness" in quantitative performance by demonstrating that the thin plate leads to very low bias error over a large range of hyperparameters, while keeping a reasonable variance. variance.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.6
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• pp.133-142
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• 2012

The objective of this study was to correct the bias of the Representative Concentration Pathways (RCP)-based future precipitation data using a quantile mapping method. This method was adopted to correct extreme values because it was designed to adjust simulated data using probability distribution function. The Generalized Extreme Value (GEV) distribution was used to fit distribution for precipitation data obtained from the Korea Meteorological Administration (KMA). The resolutions of precipitation data was 12.5 km in space and 3-hour in time. As the results of bias correction over the past 30 years (1976~2005), the annual precipitation was increased 16.3 % overall. And the results for 90 years (divided into 2011~2040, 2041~2070, 2071~2100) were that the future annual precipitation were increased 8.8 %, 9.6 %, 11.3 % respectively. It also had stronger correction effects on high value than low value. It was concluded that a quantile mapping appeared a good method of correcting extreme value.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.417-427
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• 2015

Measures in response rate used to measure the representativeness of the sample (the more high response rate) better explain the representativeness of the sample. However, we cannot often explain the representativeness of the sample because there is nonresponse even in the high response rate. Therefore, Schouten et al. (2009) presented a new R-indicator measure that can be described as a representative of the sample. We research the new estimator of the R-indicator in this paper because there are parameters that require estimations. We describe the meanings as representative of the R-indicator; consequently, the bias and efficiency of the proposed estimator for R-indicator are compared to the existing estimator under various simulations. The representativeness of the sample is also explained by applying the proposed estimators in the actual data.

• Environmental and Resource Economics Review
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• v.28 no.4
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• pp.645-673
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• 2019

The hypothetical nature of stated preferences can lead to a hypothetical bias that might work as a normative pressure, influencing survey responses. This paper aims to test the impact of social desirability bias by comparing economic estimates based on both subjective and objective valuation questions. The case study is about an urban riverine restoration project in Deajeon, South Korea. As valuation methods both contingent valuation and choice experiments were comparatively applied. Based on a nationally representative sample of 1,000 respondents, the test results offered contrasting conclusions between two test approaches. Accroding to the estimation results based on the conventional valuation, the marginal willingness to pay estimates are 10,500 KRW from CV; and 18,600 KRW for improving water quality, 2,200 KRW for the inside view, 8,900 KRW for the outside view, and 5,800 KRW for biodiversity from CE. A segmentation-based approach is a conventionally used method, which showed a limited impact of social desirability on willingness to pay estimates. The alternative parameterization-based approach measures a model-wide impact of social desirability, proving a significant bias. Although the study positioned a cheap-talk statement before the valuation section of the survey questionnaires, which might have pre-screened the bias, the overall implications of the results suggest a caution in reducing and observing hypothetical bias. There might remain a significant and substantial hypothetical bias even after cheap-talk, particularly in situations with strong social desirability, so that the potential role of objective valuation questions is guaranteed.

• The Journal of Fisheries Business Administration
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• v.47 no.3
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• pp.71-92
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• 2016

This study examines the effects of consumer beliefs for food certifications on the behavioral intentions and the behavioral intention biases to purchase the certified seafoods by a subjective probability model which is on the basis of the mathematical probability model and the covariance model. The food certifications used on this study are 'Organic foods', 'Traceability system of food products' and. 'HACCP'. The representative foods of fishery products on this study is seasoned laver. The current study showed the following results. First, consumers have more than two different beliefs each for all certifications which are the subjects of this study. The beliefs of the certifications have an impact on the consumers when they consider to buy the certified seafood products. Second, consumers try to persuade by themselves to ensure that their particular belief about the certification could lead to a purchase the seafood products. Consumer beliefs of the "environmentally friendly production" on the organic foods certification is an important factor as much as the "guarantee of food safety" belief making a positive purchasing behavior intentions(PBI) bias for the organic seafood products. Consumers also have a positive PBI bias for certified seafood products in all certifications as long as a certification is considered to "guarantee the transparency of the food distribution process" as its belief. 'Traceability system' was the only one which didn't generate a positive PBI bias from the belief of "guarantee of food safety" out of three certifications.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5C
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• pp.343-350
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• 2006

The resistance bias factors for driven steel pipe piles are evaluated as a part of study to develop the LRFD(Load and Resistance Factor Design) for foundation structures in Korea. The 43 data sets of static load tests and soil property tests performed in the whole domestic area were collected and analyzed to determine the representative bearing capacities of the piles using various methods. Based on the statistical analysis of the data, the Davisson's criterion is proved to be the most reasonable method for estimation of pile bearing capacity among the methods used. The static bearing capacity formulas and the Meyerhof method using N values are applied to calculate the design bearing capacity of the piles. The resistance bias factors of the driven steel pipe piles are evaluated respectively as 0.98 and 1.46 by comparison of the bearing capacities for both of the static bearing capacity formulas and the Meyerhof method. It is also shown that uncertainty of the static bearing capacity formulas is relatively less than that of the Meyerhof method.