Search results

1 – 10 of over 2000
To view the access options for this content please click here
Book part
Publication date: 10 April 2019

Heng Chen and Q. Rallye Shen

Sampling units for the 2013 Methods-of-Payment survey were selected through an approximate stratified two-stage sampling design. To compensate for nonresponse and…

Abstract

Sampling units for the 2013 Methods-of-Payment survey were selected through an approximate stratified two-stage sampling design. To compensate for nonresponse and noncoverage and ensure consistency with external population counts, the observations are weighted through a raking procedure. We apply bootstrap resampling methods to estimate the variance, allowing for randomness from both the sampling design and raking procedure. We find that the variance is smaller when estimated through the bootstrap resampling method than through the naive linearization method, where the latter does not take into account the correlation between the variables used for weighting and the outcome variable of interest.

Details

The Econometrics of Complex Survey Data
Type: Book
ISBN: 978-1-78756-726-9

Keywords

To view the access options for this content please click here
Article
Publication date: 16 March 2020

Muhamad Husnain Mohd Noh, Mohd Akramin Mohd Romlay, Chuan Zun Liang, Mohd Shamil Shaari and Akiyuki Takahashi

Failure of the materials occurs once the stress intensity factor (SIF) overtakes the material fracture toughness. At this level, the crack will grow rapidly resulting in…

Abstract

Purpose

Failure of the materials occurs once the stress intensity factor (SIF) overtakes the material fracture toughness. At this level, the crack will grow rapidly resulting in unstable crack growth until a complete fracture happens. The SIF calculation of the materials can be conducted by experimental, theoretical and numerical techniques. Prediction of SIF is crucial to ensure safety life from the material failure. The aim of the simulation study is to evaluate the accuracy of SIF prediction using finite element analysis.

Design/methodology/approach

The bootstrap resampling method is employed in S-version finite element model (S-FEM) to generate the random variables in this simulation analysis. The SIF analysis studies are promoted by bootstrap S-version Finite Element Model (BootstrapS-FEM). Virtual crack closure-integral method (VCCM) is an important concept to compute the energy release rate and SIF. The semielliptical crack shape is applied with different crack shape aspect ratio in this simulation analysis. The BootstrapS-FEM produces the prediction of SIFs for tension model.

Findings

The mean of BootstrapS-FEM is calculated from 100 samples by the resampling method. The bounds are computed based on the lower and upper bounds of the hundred samples of BootstrapS-FEM. The prediction of SIFs is validated with Newman–Raju solution and deterministic S-FEM within 95 percent confidence bounds. All possible values of SIF estimation by BootstrapS-FEM are plotted in a graph. The mean of the BootstrapS-FEM is referred to as point estimation. The Newman–Raju solution and deterministic S-FEM values are within the 95 percent confidence bounds. Thus, the BootstrapS-FEM is considered valid for the prediction with less than 6 percent of percentage error.

Originality/value

The bootstrap resampling method is employed in S-FEM to generate the random variables in this simulation analysis.

Details

International Journal of Structural Integrity, vol. 11 no. 4
Type: Research Article
ISSN: 1757-9864

Keywords

To view the access options for this content please click here
Article
Publication date: 18 February 2021

Wenguang Yang, Lianhai Lin and Hongkui Gao

To solve the problem of simulation evaluation with small samples, a fresh approach of grey estimation is presented based on classical statistical theory and grey system…

Abstract

Purpose

To solve the problem of simulation evaluation with small samples, a fresh approach of grey estimation is presented based on classical statistical theory and grey system theory. The purpose of this paper is to make full use of the difference of data distribution and avoid the marginal data being ignored.

Design/methodology/approach

Based upon the grey distribution characteristics of small sample data, the definition about a new concept of grey relational similarity measure comes into being. At the same time, the concept of sample weight is proposed according to the grey relational similarity measure. Based on the new definition of grey weight, the grey point estimation and grey confidence interval are studied. Then the improved Bootstrap resampling is designed by uniform distribution and randomness as an important supplement of the grey estimation. In addition, the accuracy of grey bilateral and unilateral confidence intervals is introduced by using the new grey relational similarity measure approach.

Findings

The new small sample evaluation method can realize the effective expansion and enrichment of data and avoid the excessive concentration of data. This method is an organic fusion of grey estimation and improved Bootstrap method. Several examples are used to demonstrate the feasibility and validity of the proposed methods to illustrate the credibility of some simulation data, which has no need to know the probability distribution of small samples.

Originality/value

This research has completed the combination of grey estimation and improved Bootstrap, which makes more reasonable use of the value of different data than the unimproved method.

Details

Grey Systems: Theory and Application, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2043-9377

Keywords

To view the access options for this content please click here
Article
Publication date: 5 February 2018

Haoliang Wang, Xiwang Dong, Qingdong Li and Zhang Ren

By using small reference samples, the calculation method of confidence value and prediction method of confidence interval for multi-input system are investigated. The…

Abstract

Purpose

By using small reference samples, the calculation method of confidence value and prediction method of confidence interval for multi-input system are investigated. The purpose of this paper is to offer effective assessing methods of confidence value and confidence interval for the simulation models used in establishing guidance and control systems.

Design/methodology/approach

In this paper, first, an improved cluster estimation method is proposed to guide the selection of the small reference samples. Then, based on analytic hierarchy process method, the new calculation method of the weight of each reference sample is derived. By using the grey relation analysis method, new calculation methods of the correlation coefficient and confidence value are presented. Moreover, the confidence interval of the sample awaiting assessment is defined. A new prediction method is derived to obtain the confidence interval of the sample awaiting assessment which has no reference sample. Subsequently, by using the prediction method and original small reference samples, Bootstrap resampling method is used to obtain more correlation coefficients for the sample to reduce the probability of abandoning the true.

Findings

The grey relational analysis is used in assessing the confidence value and interval prediction. The numerical simulations are presented to demonstrate the effectiveness of the theoretical results.

Originality/value

Based on the selected small reference samples, new calculation methods of the correlation coefficient and confidence value are presented to assess the confidence value of model awaiting assessment. The calculation methods of maximum confidence interval, expected confidence interval and other required confidence intervals are presented, which can be used in assessing the validities of controller and guidance system obtained from the model awaiting assessment.

Details

Grey Systems: Theory and Application, vol. 8 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

To view the access options for this content please click here
Article
Publication date: 7 August 2017

Bahram Sadeghpour Gildeh, Sedigheh Rahimpour and Fatemeh Ghanbarpour Gravi

The purpose of this paper is to construct a statistical hypotheses test for process capability indices and compare the pairs of them with a fixed sample size.

Abstract

Purpose

The purpose of this paper is to construct a statistical hypotheses test for process capability indices and compare the pairs of them with a fixed sample size.

Design/methodology/approach

Since the sampling distribution of the estimators of pairs of two process capability indices (PCIs) is very complex, an exact statistical hypothesis test for them cannot be constructed. Therefore, the authors have proposed a bootstrap method to construct the hypothesis test for them on the basis of p-value.

Findings

The authors have shown that by increasing n, the bootstrap method has better output relative to other methods and it can be easily implemented. The authors have also demonstrated that sometimes an exact hypotheses test cannot be constructed and need some assumptions.

Originality/value

In the present paper, several methods to test of hypotheses about the difference between two process capability indices have been compared.

Details

International Journal of Quality & Reliability Management, vol. 34 no. 7
Type: Research Article
ISSN: 0265-671X

Keywords

To view the access options for this content please click here
Article
Publication date: 15 June 2020

Modisane Bennett Seitshiro and Hopolang Phillip Mashele

The purpose of this paper is to propose the parametric bootstrap method for valuation of over-the-counter derivative (OTCD) initial margin (IM) in the financial market…

Abstract

Purpose

The purpose of this paper is to propose the parametric bootstrap method for valuation of over-the-counter derivative (OTCD) initial margin (IM) in the financial market with low outstanding notional amounts. That is, an aggregate outstanding gross notional amount of OTC derivative instruments not exceeding R20bn.

Design/methodology/approach

The OTCD market is assumed to have a Gaussian probability distribution with the mean and standard deviation parameters. The bootstrap value at risk model is applied as a risk measure that generates bootstrap initial margins (BIM).

Findings

The proposed parametric bootstrap method is in favour of the BIM amounts for the simulated and real data sets. These BIM amounts are reasonably exceeding the IM amounts whenever the significance level increases.

Research limitations/implications

This paper only assumed that the OTCD returns only come from a normal probability distribution.

Practical implications

The OTCD IM requirement in respect to transactions done by counterparties may affect the entire financial market participants under uncleared OTCD, while reducing systemic risk. Thus, reducing spillover effects by ensuring that collateral (IM) is available to offset losses caused by the default of a OTCDs counterparty.

Originality/value

This paper contributes to the literature by presenting a valuation of IM for the financial market with low outstanding notional amounts by using the parametric bootstrap method.

Details

The Journal of Risk Finance, vol. 21 no. 5
Type: Research Article
ISSN: 1526-5943

Keywords

To view the access options for this content please click here
Article
Publication date: 8 February 2016

Louie Ren and Peter Ren

The purpose of this paper is to look at the power of the Student t-test applied to two independent samples when returns from AR(1) process are categorized into two samples…

Abstract

Purpose

The purpose of this paper is to look at the power of the Student t-test applied to two independent samples when returns from AR(1) process are categorized into two samples by moving average buy-sell trading rule.

Design/methodology/approach

Simulation and empirical study for returns from NASDAQ via bootstrapping resampling method are conducted.

Findings

The authors conclude that applying the MA Trading Rule followed by Student t-test is not appropriate for analyzing market efficiency.

Originality/value

Moving average buy-sell trading rule is widely used in finance to test if the market is efficient. In this paper, it is one of the first kind of research to examine the power of the test via simulation and empirical study.

Details

Managerial Finance, vol. 42 no. 2
Type: Research Article
ISSN: 0307-4358

Keywords

To view the access options for this content please click here
Article
Publication date: 21 March 2016

Anoop Patiar and Ying Wang

This paper aims to examine the effects of hotel general managers’ transformational leadership (TLS) and department managers (DMs)’ organizational commitment (OC) on their…

Abstract

Purpose

This paper aims to examine the effects of hotel general managers’ transformational leadership (TLS) and department managers (DMs)’ organizational commitment (OC) on their department’s performance in upscale hotels in Australia.

Design/methodology/approach

Data were collected by surveying DMs in four- and five-star hotels. The survey instrument included measures of comprehensive sustainable performance, TLS and OC adapted from the literature. The data were analyzed through factor analysis and regression with a resampling method of bootstrapping.

Findings

The findings indicated that TLS influenced hotel departments’ non-financial as well as social and environmental performance dimensions directly and indirectly through OC. However, the mediation effect of OC did not exist for financial performance.

Research limitations/implications

The key theoretical contribution is the use of performance assessment based on critical success factors of hotel businesses and the bootstrapping regression model.

Practical implications

Senior managers should pay attention to TLS qualities when appointing core managers, provide on-going structured TLS training and concentrate on leading performance dimensions for performance assessment.

Originality/value

This study responds to the call for leadership research to move beyond its emphasis on individual performance and to address performance more holistically by considering its multidimensionality and the processes underlying effective performance.

Details

International Journal of Contemporary Hospitality Management, vol. 28 no. 3
Type: Research Article
ISSN: 0959-6119

Keywords

To view the access options for this content please click here
Article
Publication date: 18 May 2012

Patthareeya Lakpetch and Tippawan Lorsuwannarat

This paper attempts to propose an integrated model for measuring the knowledge transfer effectiveness in university‐industry alliances. The so‐called “RDCE” model is…

Abstract

Purpose

This paper attempts to propose an integrated model for measuring the knowledge transfer effectiveness in university‐industry alliances. The so‐called “RDCE” model is thereby proposed as an integrated model for measuring the knowledge transfer effectiveness. By combining inter‐organizational relations (IORs), knowledge‐based view (KBV) and resource‐based view (RBV) of firms, this paper aims to focus on the influence of determinant factors such as partner complementarities, partner attributes, the characteristics of the coordination and relationship quality between industrial companies and universities that may lead to the effectiveness of knowledge transfer.

Design/methodology/approach

This framework thereby clarifies how mediating variables influenced the paths that constitute the direct, indirect and total effects of mediated models by integrating moderated regression analysis together with bootstrap resampling methods to ensure the precision in estimating confidence intervals of indirect effects and path analysis using structural equation models to test all the hypotheses simultaneously for the robustness of the results and conclusions.

Findings

The statistical results reveal that the proposed model has a significant mediating effect that contributes to knowledge transfer effectiveness. Only partner attributes and relationship factors have a direct impact on the effectiveness of knowledge transfer. This appears plausible since mere complementarities and coordination between partners may not lead to learning or knowledge transfer, which requires a certain depth of the partner interaction in terms of the specific attributes of partners, coordination and relationship quality.

Research limitations/implications

The authors assumed that the alliance constitutes partnerships between firms of roughly equal size and market power. Therefore, this study provided only broad perspectives of collaboration among alliance partners, and did not capitalize on different degree of alliance integration and different types of collaboration.

Practical implications

Managerial suggestions on how to improve their knowledge transfer effectiveness are also provided at the end of the text.

Originality/value

There are numerous studies examining alliance network performance. Very few studies, however, have examined detailed collaborative activities in dyadic university‐industry partnerships and potential constructs for measuring knowledge transfer and commercialization in the research and development alliance between industrial firms and university context.

Content available
Article
Publication date: 14 January 2019

S. Mostafa Rasoolimanesh and Faizan Ali

Abstract

Details

Journal of Hospitality and Tourism Technology, vol. 9 no. 3
Type: Research Article
ISSN: 1757-9880

1 – 10 of over 2000