• Title/Summary/Keyword: bootstrapping method

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Element of Marketing: SERVQUAL Toward Patient Loyalty in the Private Hospital Sector

  • AKOB, Muhammad;YANTAHIN, Munawar;ILYAS, Gunawan Bata;HALA, Yusriadi;PUTRA, Aditya Halim Perdana Kusuma
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.1
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    • pp.419-430
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    • 2021
  • The study aims to analyze the factors that shape patient loyalty, namely, by involving the service quality factor (SERVQUAL), hospital image, patient value, and patient satisfaction in private hospitals. This study was conducted in Makassar City, Indonesia, with a sample of 296 eligible samples from private hospitals. The sample criteria were patients with outpatient and hospitalization status. Then, this study developed 23 hypotheses to test the statistical relationship between direct, intervening and multiple-effect models. Problem-solving and research focus are carried out using a quantitative method approach with a PLS-SEM-based testing tool. The bootstrapping method is being used with the constant bootstrapping step to demonstrate the results of hypothesis testing; we find that the overall hypothesis has a positive and significant effect. The combination of testing models involving several variables shows that a patient's loyalty can be formed if a patient's satisfaction has been realized. Satisfaction can be realized if the value-customer has been felt by the patients. Therefore, the hospital image must be directly proportional to service quality. Service quality is the essence of service that directly affects customers; service quality is also the reason that shapes consumer perceptions in increasing rationalization and solid customer (patient's) decision-making.

Influence of Parental Attachment on Learning Flow: Mediating Effects of Parental Academic Expectation and Optimism in Adolescents (청소년들의 부모애착이 학습몰입에 미치는 영향: 부모의 학업기대와 낙관성의 매개효과)

  • Jeong, Goo-Churl;Seol, Mi-Kyung
    • Journal of the Korea Convergence Society
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    • v.10 no.7
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    • pp.213-224
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    • 2019
  • The purpose of this study was to analyze the mediating effects of parental academic expectations and adolescent's optimism in the influence of perceived parental attachment on learning flow. The subjects of this study were 184 middle and high school students in Seoul. The results of this study are as follows. First, academic expectation and optimism showed significant full mediation effects on the relationship between parent attachment and learning flow. Second, there was no statistically significant difference in the difference between the indirect effects of academic expectation and optimism by the bootstrapping method. Based on the results of this study, it was found that the healthy attachment relationship with the parents increases the parent's supportive expectancy, improves the optimism for the youth, and improves the learning commitment for effective learning. Finally, we discussed the role and expectations of parents and adolescents in promoting the learning commitment of adolescents.

Double Bootstrap Confidence Cones for Sphericla Data based on Prepivoting

  • Shin, Yang-Kyu
    • Journal of the Korean Statistical Society
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    • v.24 no.1
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    • pp.183-195
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    • 1995
  • For a distribution on the unit sphere, the set of eigenvectors of the second moment matrix is a conventional measure of orientation. Asymptotic confidence cones for eigenvector under the parametric assumptions for the underlying distributions and nonparametric confidence cones for eigenvector based on bootstrapping were proposed. In this paper, to reduce the level error of confidence cones for eigenvector, double bootstrap confidence cones based on prepivoting are considered, and the consistency of this method is discussed. We compare the perfomances of double bootstrap method with the others by Monte Carlo simulations.

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A Unit Root Test Based on Bootstrapping

  • Shin, Key-Il;Kang, Hee-Jeong
    • Communications for Statistical Applications and Methods
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    • v.3 no.1
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    • pp.257-265
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    • 1996
  • We consider nonstationary autoregressive autoregressive process with infinite variance of error. In the case of infinite cariance, the limiting distribution of the estimated coefficient is different from that under the finite cariance assumption. In this paper we show that the bootstrap method can be used to approximate the distribution of ordinary least squares estimator of the coefficient in the first order random walk process with infinite variance through some empirical studies and we suggest a test procedure based on bootstrap method for the unit root test.

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On Bootstrapping; Bartlett Adjusted Empirical Likelihood Ratio Statistic in Regression Analysis

  • Woochul Kim;Duk-Hyun Ko;Keewon Lee
    • Journal of the Korean Statistical Society
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    • v.25 no.2
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    • pp.205-216
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    • 1996
  • The bootstrap calibration method for empirical likelihood is considered to make a confidence region for the regression coefficients. Asymptotic properties are studied regarding the coverage probability. Small sample simulation results reveal that the bootstrap calibration works quite well.

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Automatic Text Categorization based on Semi-Supervised Learning (준지도 학습 기반의 자동 문서 범주화)

  • Ko, Young-Joong;Seo, Jung-Yun
    • Journal of KIISE:Software and Applications
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    • v.35 no.5
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    • pp.325-334
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    • 2008
  • The goal of text categorization is to classify documents into a certain number of pre-defined categories. The previous studies in this area have used a large number of labeled training documents for supervised learning. One problem is that it is difficult to create the labeled training documents. While it is easy to collect the unlabeled documents, it is not so easy to manually categorize them for creating training documents. In this paper, we propose a new text categorization method based on semi-supervised learning. The proposed method uses only unlabeled documents and keywords of each category, and it automatically constructs training data from them. Then a text classifier learns with them and classifies text documents. The proposed method shows a similar degree of performance, compared with the traditional supervised teaming methods. Therefore, this method can be used in the areas where low-cost text categorization is needed. It can also be used for creating labeled training documents.

Device Security Bootstrapping Mechanism on the IEEE 802.15.4-Based LoWPAN (IEEE 802.15.4 기반 LoWPAN에서의 디바이스 보안 설정 메커니즘)

  • Lee, Jong-Hoon;Park, Chang-seop
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.26 no.6
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    • pp.1561-1569
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    • 2016
  • As the use of the sensor device increases in IoT environment, the need for device security is becoming more and more important When a sensor device is deployed in IEEE 802.15.4-based LoWPAN, it has to perform the join operation with PAN Coordinator and the binding operation with another device. In the join and binding process, authentication and key distribution of the device are performed using the pre-distributed network key or certificate. However, the network key used in the conventional method has problems that it's role is limited to the group authentication and individual identification is not applied in certificate issuing. In this paper, we propose a secure join and binding protocol in LoWPAN environment that solves the problems of pre-distributed network key.

A Bootstrap Lagrangian Multiplier Test for Market Microstructure Noise in Financial Assets (금융자산의 시장 미시구조 잡음에 대한 부트스트래핑 라그랑지 승수 검정)

  • Kim, Hyo Jin;Shin, Dong Wan;Park, Jonghun;Lee, Sang-Goo
    • The Korean Journal of Applied Statistics
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    • v.28 no.2
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    • pp.189-200
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    • 2015
  • Stationary bootstrapping is applied to a Lagrangian multiplier (LM) test to test market microstructure noise (MMN) in financial asset prices. A Monte-Carlo experiment shows that the bootstrapping method improves the size of the original LM test which has some size distortion for conditional heteroscedastic models. The proposed test is illustrated for real data sets like KOSPI index and Won-Dollar exchange rate.

Bootstrapping Regression Residuals

  • Imon, A.H.M. Rahmatullah;Ali, M. Masoom
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.3
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    • pp.665-682
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    • 2005
  • The sample reuse bootstrap technique has been successful to attract both applied and theoretical statisticians since its origination. In recent years a good deal of attention has been focused on the applications of bootstrap methods in regression analysis. It is easier but more accurate computation methods heavily depend on high-speed computers and warrant tough mathematical justification for their validity. It is now evident that the presence of multiple unusual observations could make a great deal of damage to the inferential procedure. We suspect that bootstrap methods may not be free from this problem. We at first present few examples in favour of our suspicion and propose a new method diagnostic-before-bootstrap method for regression purpose. The usefulness of our newly proposed method is investigated through few well-known examples and a Monte Carlo simulation under a variety of error and leverage structures.

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Bootstrapping of Hanwoo Chromosome17 Based on BMS1167 Microsatellite Locus

  • Lee, Jea-Young;Lee, Yong-Won;Yeo, Jung-Sou
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.1
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    • pp.175-184
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    • 2007
  • LOD scores and a permutation test for detecting and locating quantitative trait loci (QTL) from the Hanwoo economic trait have been described and we selected a considerable major BMS1167 locus for further analysis. K-means clustering analysis, for the major DNA marker mining of BMS1167 microsatellite loci in Hanwoo chromosome17, has been tried and three cluster groups divide four traits. The three cluster groups are classified according to eight DNA marker bps. Finally, we employed the bootstrap test method to calculate confidence intervals using the resampling method to find major DNA markers. We conclude that the major marker of BMS1167 locus in Hanwoo chromosome17 is only DNA marker 100bp.

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