scholarly journals Estimation of Uncertainty in Airborne LiDAR Inventories Using Approaches Based on Bootstrapping-Pairs Methods

Forests ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1305
Author(s):  
Simón Sandoval ◽  
Ramón Bustamante-Ortega
Keyword(s):  
Bootstrap Method ◽  
Airborne Lidar ◽  
Population Estimates ◽  
Residual Variance ◽  
Average Volume ◽  
Pair Method ◽  
The Mean ◽  
Variance Estimates ◽  
The Relationship ◽  
The Bootstrap Method

LiDAR inventories were carried out to estimate the mean volume and variance in Eucalyptus globulus and Eucalyptus nitens stands. Uncertainty of the population estimates was examined using approximations based on the bootstrap method. Three methods were tested, the traditional bootstrapping-pair method (Method 1) and two additional methods in which the residual variance of the models was incorporated. Method 2 incorporated the residual variance in homoscedastic structure and Method 3 incorporated the heteroscedastic residual variance. Bootstrapping-pairs based on Method 3 generated similar estimates for the mean volume and slightly higher estimates for the variance as the traditional method (Method 1). Variance estimates obtained with the traditional bootstrapping-pairs method could be biased due to the presence of heteroscedasticity. Method 3 was found to best estimate the variance of the mean volume in LiDAR inventories, when the models that describe the relationship between stand variables and LiDAR metrics do not meet the assumption of homoscedasticity. It is shown that the uncertainty of the estimation of the average volume decreased in stands with a larger area, stabilizing the uncertainty of estimates in stands with areas larger than 50 hectares. Our results suggest that the residual variance in the heteroscedastic structure must be incorporated to avoid bias when bootstrapping-pairs are used in small area stands (less than 5 hectares).

The Bootstrap-Method: Discussion and Proposal for Improvement / Das bootstrap-Verfahren: Diskussion und Verbesserungsvorschlag

1998 ◽  
Vol 217 (1) ◽  
Author(s):  
Hans Schneeberger
Keyword(s):  
Bootstrap Method ◽  
Law School ◽  
Mean Deviation ◽  
Alternative Method ◽  
Doubling Method ◽  
The Mean ◽  
The Bootstrap Method

SummaryWith Efron’s law-school example the bootstrap method is compared with an alternative method, called doubling. It is shown, that the mean deviation of the estimator is always smaller for the doubling method.

scholarly journals Conservative Estimations of Reliability With Limited Sampling

2007 ◽  
Author(s):  
Victor Picheny ◽  
Nam-Ho Kim ◽  
Raphael T. Haftka
Keyword(s):  
Normal Distribution ◽  
Thermal Loading ◽  
Bootstrap Method ◽  
Composite Panel ◽  
Small Samples ◽  
Normal Distribution Function ◽  
Limited Sampling ◽  
Bootstrap Approach ◽  
The Relationship ◽  
The Bootstrap Method

The objective of this paper is to provide a method of safely estimating reliability based on small samples. First, it is shown that the commonly used estimators of the parameters of the normal distribution function are biased, and they tend to lead to unconservative estimates of reliability. Then, two ways of making this estimation conservative are proposed: (1) adding constraints when a distribution is fitted to the data to bias it to be conservative, and (2) using the bootstrap method to estimate the bias needed for a given level of conservativeness. The relationship between the accuracy and the conservativeness of the estimates is explored for a normal distribution. In particular, detailed results are presented for the case when the goal is 95% likelihood to be conservative. The bootstrap approach is found to be more accurate for this level of conservativeness. It is then applied to the reliability analysis of a composite panel under thermal loading. Finally, we explore the influence of sample sizes and target probability of failure on estimates quality, and show that for a constant level of conservativeness, small samples and low probabilities can lead to a high risk of large overestimation while this risk is limited to a very reasonable value for samples above.

scholarly journals Antecedents and consequence associated with esports gameplay

2019 ◽  
Vol 21 (1) ◽  
pp. 1-22 ◽  
Author(s):  
Wooyoung (William) Jang ◽  
Kevin K. Byon
Keyword(s):  
Bootstrap Method ◽  
Media Consumption ◽  
Temporal Separation ◽  
Content Type ◽  
Perceived Effort ◽  
Use Of Technology ◽  
Proposed Model ◽  
Effort Expectancy ◽  
The Relationship ◽  
The Bootstrap Method

Purpose Grounded in the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) (Venkatesh et al., 2012), the purpose of this paper is to examine the antecedents and consequence associated with esports gameplay by proposing the Esports Consumption (ESC) model, including six determinants of esports gameplay intention (hedonic motivation, habit, price value, perceived effort expectancy, social influence and flow) and behavioral consequence (media consumption intention of esports events) that were linked to esports gameplay. Design/methodology/approach The proposed model was tested using the data (n=348) that were collected from esports consumers at two points in time. Per the technology adoption theories (i.e. TAM, UTAUT2), the authors incorporated a temporal separation when measuring the relationship between playing intention and playing behavior. For the purpose of data analysis, CFA and SEM were used to examine the hypothesized model. Findings As a result, four determinants (i.e. hedonic motivation, price value, effort expectancy and flow) were identified as the critical factors influencing esports consumers’ esports gameplay intention. Furthermore, the bootstrap method procedure verified that a sequential relationship among esports gameplay intention, esports gameplay and media consumption of esports events. Originality/value Theoretically, it has developed a research model that explains various triggers resulting from esports gameplay intention, which is causally linked to esports gameplay and media consumption behavior. Practically, the primary implication has to do with providing information regarding esports consumers’ playing behavior with esports game publishers, which organize esports events and leagues.

scholarly journals Comparison of the Bootstrap and Delta Method Variances of the Variance Estimator of the Bernoulli Distribution

2018 ◽  
pp. 1-10
Author(s):  
Ying- Ying Zhang ◽  
Teng- Zhong Rong ◽  
Man- Man Li
Keyword(s):  
Bootstrap Method ◽  
Delta Method ◽  
Variance Estimator ◽  
Bernoulli Distribution ◽  
Bernoulli Trials ◽  
The Absolute ◽  
Variance Estimates ◽  
Parameter Values ◽  
The Bootstrap Method

It is interesting to calculate the variance of the variance estimator of the Bernoulli distribution. Therefore, we compare the Bootstrap and Delta Method variances of the variance estimator of the Bernoulli distribution in this paper. Firstly, we provide the correct Bootstrap, Delta Method, and true variances of the variance estimator of the Bernoulli distribution for three parameter values in Table 2.1. Secondly, we obtain the estimates of the variance of the variance estimator of the Bernoulli distribution by the Delta Method (analytically), the true method (analytically), and the Bootstrap Method (algorithmically). Thirdly, we compare the Bootstrap and Delta Methodsin terms of the variance estimates, the errors, and the absolute errors in three gures for 101 parameter values in [0, 1], with the purpose to explain the di erences between the Bootstrap and Delta Methods. Finally, we give three examples of the Bernoulli trials to illustrate the three methods.

scholarly journals The Effect of Perceived Over-Qualification on Turnover Intention From a Cognition Perspective

2021 ◽  
Vol 12 ◽  
Author(s):  
Guofu Chen ◽  
Yanzhao Tang ◽  
Yawen Su
Keyword(s):  
Turnover Intention ◽  
Employee Turnover ◽  
Bootstrap Method ◽  
Organizational Management ◽  
Mediating Effect ◽  
Hierarchical Regression ◽  
Theoretical Support ◽  
Employee Turnover Intention ◽  
The Relationship ◽  
The Bootstrap Method

Employee turnover caused by over-qualification has become a new problem in organizational management. The mechanism underpinning the boundaries between perceived over-qualification and employee turnover, however, remains unclear. To address this gap, the current study employed multi-factor ANOVA, hierarchical regression analysis and the bootstrap method to analyze the relationship between perceived over-qualification and employee turnover intention based on the survey data of 396 respondents in China. Overall, the results revealed that perceived over-qualification was positively correlated with turnover intention. It was also found that self-efficacy had a mediating effect on the relationship between perceived over-qualification and turnover intention. Further, professional identity had a moderating effect on the relationship between perceived over-qualification and turnover intention. Our findings expand the boundary of influence around perceived over-qualification and provide theoretical support for employee management.

scholarly journals Motivation, Social Emotion, and the Acceptance of Artificial Intelligence Virtual Assistants—Trust-Based Mediating Effects

2021 ◽  
Vol 12 ◽  
Author(s):  
Shiying Zhang ◽  
Zixuan Meng ◽  
Beibei Chen ◽  
Xiu Yang ◽  
Xinran Zhao
Keyword(s):  
Artificial Intelligence ◽  
Technology Acceptance ◽  
Bootstrap Method ◽  
Mediating Effects ◽  
Multilevel Regression ◽  
Social Emotions ◽  
Social Emotion ◽  
Acceptance Model ◽  
The Relationship ◽  
The Bootstrap Method

The complexity of the emotional presentation of users to Artificial Intelligence (AI) virtual assistants is mainly manifested in user motivation and social emotion, but the current research lacks an effective conversion path from emotion to acceptance. This paper innovatively cuts from the perspective of trust, establishes an AI virtual assistant acceptance model, conducts an empirical study based on the survey data from 240 questionnaires, and uses multilevel regression analysis and the bootstrap method to analyze the data. The results showed that functionality and social emotions had a significant effect on trust, where perceived humanity showed an inverted U relationship on trust, and trust mediated the relationship between both functionality and social emotions and acceptance. The findings explain the emotional complexity of users toward AI virtual assistants and extend the transformation path of technology acceptance from the trust perspective, which has implications for the development and design of AI applications.

scholarly journals Uncertainty of the Electricity Emission Factor Incorporating the Uncertainty of the Fuel Emission Factors

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5697
Author(s):  
Kun Mo LEE ◽  
Min Hyeok LEE
Keyword(s):  
Power Generation ◽  
Emission Factor ◽  
Bootstrap Method ◽  
Ghg Emissions ◽  
Original Data ◽  
Emission Factors ◽  
Ghg Emission ◽  
Data Set ◽  
The Mean ◽  
The Bootstrap Method

Greenhouse gas (GHG) emission from electricity generation has been recognized as one of the most significant contributors to global warming. The GHG emission factor of electricity (hereafter, electricity emission factor) can be expressed as a function of three different (average, minimum, and maximum) fuel emission factors, monthly fuel consumption, and monthly net power generation. Choosing the average fuel emission factor over the minimum and maximum fuel emission factors is the cause of uncertainty in the electricity emission factor, and thus GHG emissions of the power generation. The uncertainties of GHG emissions are higher than those of the electricity emission factor, indicating that the uncertainty of GHG emission propagates in the GHG emission computation model. The bootstrapped data were generated by applying the bootstrap method to the original data set which consists of a 60-monthly average, and minimum and maximum electricity emission factors. The bootstrapped data were used for computing the mean, confidence interval (CI), and percentage uncertainty (U) of the electricity emission factor. The CI, mean, and U were [0.431, 0.443] kg CO2-eq/kWh, 0.437 kg CO2-eq/kwh, and 2.56%, respectively.

scholarly journals Moderating Role of Job Satisfaction on Turnover Intention and Burnout among Workers in Primary Care Institutions: A Cross-Sectional study

2019 ◽  
Author(s):  
Xuyu Chen ◽  
Li Ran ◽  
Yuting Zhang ◽  
Jinru Yang ◽  
Hui Yao ◽  
...  
Keyword(s):  
Job Satisfaction ◽  
Turnover Intention ◽  
Career Planning ◽  
Bootstrap Method ◽  
Mediating Effect ◽  
Mediation Effect ◽  
Path Coefficient ◽  
The Relationship ◽  
The Bootstrap Method

Abstract Background: Global countries are suffering from a shortage of health professionals. Turnover intention is closely related to job satisfaction and burnout, making good use of these relationships could alleviate the crisis. Our research aims to examine the mediating role of job satisfaction in the relationship between burnout and turnover intention. Methods: This research was conducted in Huangpi, China. The convenience sampling method and self-administereded questionnaires were used. 1370 of valid samples were collected with 97.72% effective rate. Descriptive analyses were conducted to describe social demographic factors. The structural equation model (SEM) was performed to adjust model fitting, and the mediation effect test was carried out by using the bootstrap method. Sobel-Z test was used to verify the significance of mediation effect. Results: The mean age was 36.98 (SD=9.84). The fitting indices of hypothetical model are not good. After the adjustments, χ2/df =5.590, GFI=0.932, AGFI=0.901, CFI=0.977, NFI=0.973, IFI=0.977, TLI=0.970, RESEA=0.058. The revised model fitted well, and the SEM was put up by using the bootstrap method. The mediating effect is partial, and Soble-Z test indicates that the mediation effect is significant. Burnout is negatively correlated with job satisfaction (p<0.01) and the standardized path coefficient is -0.41. Job satisfaction is also negatively correlated with turnover intention (p<0.01) and the standardized path coefficient is -0.18. Burnout is positively correlated with turnover intention (p<0.01) and the standardized path coefficient is 0.83. Conclusions: Job satisfaction is a mediating variable that affects the relationship between burnout and turnover intention. The mediating effect was a partial mediating effect and has a low impact of 7.4%. Improving treatment and giving more promotion opportunities for workers to improve job satisfaction, conducting career planning course and paying attention to employee psychological health to reduce job burnout. The above measures may be helpful to reduce employee turnover rate and alleviating the current situation of a shortage of health personnel in China.

scholarly journals Moderating role of job satisfaction on turnover intention and burnout among workers in primary care institutions: a cross-sectional study

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Xuyu Chen ◽  
Li Ran ◽  
Yuting Zhang ◽  
Jinru Yang ◽  
Hui Yao ◽  
...  
Keyword(s):  
Job Satisfaction ◽  
Turnover Intention ◽  
Career Planning ◽  
Bootstrap Method ◽  
Mediating Effect ◽  
Mediation Effect ◽  
Path Coefficient ◽  
The Relationship ◽  
The Bootstrap Method

Abstract Background Global countries are suffering from a shortage of health professionals. Turnover intention is closely related to job satisfaction and burnout, making good use of these relationships could alleviate the crisis. Our research aims to examine the mediating role of job satisfaction in the relationship between burnout and turnover intention. Methods This research was conducted in Huangpi, China. The convenience sampling method and self-administereded questionnaires were used. 1370 of valid samples were collected with 97.72% effective rate. Descriptive analyses were conducted to describe social demographic factors. The structural equation model (SEM) was performed to adjust model fitting, and the mediation effect test was carried out by using the bootstrap method. Sobel-Z test was used to verify the significance of mediation effect. Results The mean age was 36.98 (SD = 9.84). The fitting indices of hypothetical model are not good. After the adjustments, χ2/df = 5.590, GFI = 0.932, AGFI = 0.901, CFI = 0.977, NFI = 0.973, IFI = 0.977, TLI = 0.970, RESEA = 0.058. The revised model fitted well, and the SEM was put up by using the bootstrap method. The mediating effect is partial, and Soble-Z test indicates that the mediation effect is significant. Burnout is negatively correlated with job satisfaction (p < 0.01) and the standardized path coefficient is − 0.41. Job satisfaction is also negatively correlated with turnover intention (p < 0.01) and the standardized path coefficient is − 0.18. Burnout is positively correlated with turnover intention (p < 0.01) and the standardized path coefficient is 0.83. Conclusions Job satisfaction is a mediating variable that affects the relationship between burnout and turnover intention. The mediating effect was a partial mediating effect and has a low impact of 7.4%. Improving treatment and giving more promotion opportunities for workers to improve job satisfaction, conducting career planning course and paying attention to employee psychological health to reduce job burnout. The above measures may be helpful to reduce employee turnover rate and alleviating the current situation of a shortage of health personnel in China.

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