scholarly journals Bayesian Hetero-Elasticnet (A Gibbs Sampler Approach)

2021 ◽  
Vol 47 (3) ◽  
pp. 981-987
Author(s):  
Isiaka Oloyede
Keyword(s):  
Gibbs Sampler ◽  
Performance Metrics ◽  
Asymptotic Properties ◽  
Design Matrix ◽  
Multivariate Normal ◽  
Sample Sizes ◽  
Pairwise Correlation ◽  
Heteroscedastic Error ◽  
Mcmc Simulation ◽  
Larger Sample

Combined heteroscedasticity and multicollinearity as dual non-spherical disturbances were experimented asymptotically. A Gibbs Sampler technique was used to investigate the asymptotic properties of hetero-elasticnet estimator with mean squares error (MSE) and bias as performance metrics. The seed was set to 12345;  is set at ; Xs variables were generated as follow: the design matrix was generated from the multivariate normal distribution with mean > 0 and variance .  and  are truncated with Harvey (1976) heteroscedastic error structure;  are collinear covariate with pairwise correlation between 0.6 and 0.9, the sample sizes were 25, 100 and 1000. The number of replications of the experiment was set at 10,000 with burn-in of 1000 which specified the draws that were discarded to remove the effects of the initial values. The thinning was set at 5 to ensure the removal of the effects of autocorrelation in the MCMC simulation. The study found that there is consistency of estimator asymptotically as the sample sizes increases from 25 to 50 so also to 1000, the larger sample size depicted least bias. The estimator exhibited efficiency asymptotically as larger sample sizes depicted least mean squares error. The study therefore recommended Bayesian hetero-elasticnet when data exhibit both heteroscedasticity and multicollinearity. Keywords: Elasticnet; Bayesian Inference and Gibbs sampler

How Strong Is the Evidence for the Effectiveness of Working Memory Training?

2019 ◽  
pp. 58-76
Author(s):  
Claudia C. von Bastian ◽  
Sabrina Guye ◽  
Carla De Simoni
Keyword(s):  
Working Memory ◽  
Cognitive Abilities ◽  
Small Sample ◽  
Sound Studies ◽  
Working Memory Training ◽  
Memory Training ◽  
Sample Sizes ◽  
Small Sample Sizes ◽  
Transfer Tasks ◽  
Larger Sample

This chapter argues that the question of whether working memory training can induce cognitive plasticity in terms of transfer effects cannot be conclusively answered yet due to persisting methodological issues across the literature. The shortcomings discussed include the lack of theoretically motivated selection of training and transfer tasks, the lack of active control groups, and small sample sizes. These problems call into question the strength of the existing evidence. Indeed, reevaluating published findings with Bayesian inference indicated that only a subset of published studies contributed interpretable evidence. The chapter concludes that the current body of literature cannot conclusively support claims that WM training does or does not improve cognitive abilities and stresses the need for theory-driven, methodologically sound studies with larger sample sizes.

A Longitudinal Field Investigation of Auditor Risk Assessments and Sample Size Decisions

2003 ◽  
Vol 78 (4) ◽  
pp. 983-1002 ◽  
Author(s):  
Randal J. Elder ◽  
Robert D. Allen
Keyword(s):  
Sample Size ◽  
Field Investigation ◽  
Risk Assessments ◽  
Sample Sizes ◽  
Accounting Firms ◽  
Inherent Risk ◽  
Changes In Risk ◽  
Larger Sample ◽  
Average Sample ◽  
Do So

This study examines changes in auditor risk assessments and sample size decisions based on information gathered from three large accounting firms for audits during 1994 and 1999. The five-year interval between data collection periods allows us to measure changes in risk assessments and sample sizes between the two periods. Auditors relied on controls and assessed inherent risk below the maximum on most audits, and were more likely to do so in the later period, consistent with a trend of lower risk assessment levels. Average sample sizes declined between 1994 and 1999 for the firms that had larger sample sizes in the earlier period. Overall, we find a significant relationship between inherent risk assessments and sample sizes, but this relationship is stronger in the earlier period and is not significant for all firms, especially in the later period. We find limited evidence of a relationship between control risk and sample sizes.

scholarly journals The Impact of Improved Microarray Coverage and Larger Sample Sizes on Future Genome-Wide Association Studies

2013 ◽  
Vol 37 (4) ◽  
pp. 383-392 ◽  
Author(s):  
Karla J. Lindquist ◽  
Eric Jorgenson ◽  
Thomas J. Hoffmann ◽  
John S. Witte
Keyword(s):  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Sample Sizes ◽  
Genome Wide ◽  
The Impact ◽  
Larger Sample

Sample sizes for comparing means of two multivariate normal populations

1987 ◽  
Vol 16 (4) ◽  
pp. 1207-1218 ◽  
Author(s):  
Paul Speckman ◽  
Sharon Anderson ◽  
John Hewett
Keyword(s):  
Multivariate Normal ◽  
Sample Sizes ◽  
Normal Populations

scholarly journals A correction to the exact test based on the Ewens sampling distribution

1996 ◽  
Vol 68 (3) ◽  
pp. 259-260 ◽  
Author(s):  
Montgomery Slatkin
Keyword(s):  
Small Sample ◽  
Sampling Distribution ◽  
Sample Sizes ◽  
Exact Test ◽  
Small Sample Sizes ◽  
Larger Sample

SummaryThe exact test for neutrality based on the Ewens sampling distribution described previously (Slatkin, 1994) is not correct. The problem is that the test as described is based on the probability of the ordered configuration of numbers of alleles, while it should be based on the probability of the unordered configuration. The correctly implemented exact test leads to results that are similar to those from the homozygosity test proposed by Watterson (1977) for relatively small sample sizes but can still differ substantially for larger sample sizes. Programs to perform the exact test are available from the author.

scholarly journals Sample Size to Estimate the Mean and Median of Traits in Canola

2018 ◽  
Vol 10 (11) ◽  
pp. 123
Author(s):  
Alberto Cargnelutti Filho ◽  
Cleiton Antonio Wartha ◽  
Jéssica Andiara Kleinpaul ◽  
Ismael Mario Marcio Neu ◽  
Daniela Lixinski Silveira
Keyword(s):  
Sample Size ◽  
Aerial Part ◽  
Dry Matter ◽  
Central Tendency ◽  
Sample Sizes ◽  
Brassica Napus L ◽  
Fresh Matter ◽  
The Mean ◽  
Productive Traits ◽  
Larger Sample

The aim of this study was to determine the sample size (i.e., number of plants) required to estimate the mean and median of canola (Brassica napus L.) traits of the Hyola 61, Hyola 76, and Hyola 433 hybrids with precision levels. At 124 days after sowing, 225 plants of each hybrid were randomly collected. In each plant, morphological (plant height) and productive traits (number of siliques, fresh matter of siliques, fresh matter of aerial part without siliques, fresh matter of aerial part, dry matter of siliques, dry matter of aerial part without siliques, and dry matter of aerial part) were measured. For each trait, measures of central tendency, variability, skewness, and kurtosis were calculated. Sample size was determined by resampling with replacement of 10,000 resamples. The sample size required for the estimation of measures of central tendency (mean and median) varies between traits and hybrids. Productive traits required larger sample sizes in relation to the morphological traits. Larger sample sizes are required for the hybrids Hyola 433, Hyola 61, and Hyola 76, in this sequence. In order to estimate the mean of canola traits of the Hyola 61, Hyola 76 e Hyola 433 hybrids with the amplitude of the confidence interval of 95% equal to 30% of the estimated mean, 208 plants are required. Whereas 661 plants are necessary to estimate the median with the same precision.

scholarly journals High-Low Level Support Vector Regression Prediction Approach (HL-SVR) for Data Modeling with Input Parameters of Unequal Sample Sizes

2021 ◽  
pp. 2150029
Author(s):  
Maolin Shi ◽  
Liye Lv ◽  
Zhenggang Guo ◽  
Wei Sun ◽  
Xueguan Song ◽  
...  
Keyword(s):  
Support Vector Regression ◽  
Data Modeling ◽  
Support Vector ◽  
Sample Sizes ◽  
Low Level ◽  
Input Parameters ◽  
High Level ◽  
Prediction Approach ◽  
Larger Sample ◽  
Unequal Sample Sizes

Support vector regression (SVR) has been widely used to reduce the high computational cost of computer simulation. SVR assumes the input parameters have equal sample sizes, but unequal sample sizes are often encountered in engineering practices. To solve this issue, a new prediction approach based on SVR, namely as high-low level SVR approach (HL-SVR) is proposed for data modeling of input parameters of unequal sample sizes in this paper. The proposed approach consists of low-level SVR models for the input parameters of larger sample sizes and high-level SVR model for the input parameters of smaller sample sizes. For each training point of the input parameters of smaller sample sizes, one low-level SVR model is built based on its corresponding input parameters of larger sample sizes and their responses of interest. The high-level SVR model is built based on the obtained responses from the low-level SVR models and the input parameters of smaller sample sizes. A number of numerical examples are used to validate the performance of HL-SVR. The experimental results indicate that HL-SVR can produce more accurate prediction results than SVR. The proposed approach is applied to the stress analysis of dental implant, in which the structural parameters have massive samples but the material of implant can only be selected from Ti and its alloys. The obtained prediction results of the HL-SVR approach are much better than SVR. The proposed approach can be used for the design, optimization, and analysis of engineering systems with input parameters of unequal sample sizes.

scholarly journals Clinical Efficacy Analysis of Two Different Surgical Approaches to Laparoscopic Radical Cystectomy with Urinary Diversion for Invasive Bladder Cancer

2020 ◽  
pp. 1-5
Author(s):  
Li-feng Zhang ◽  
Bowen Tang ◽  
Shenglin Gao ◽  
Jiasheng Chen ◽  
Chao Lu ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Radical Cystectomy ◽  
Clinical Efficacy ◽  
Invasive Bladder Cancer ◽  
Intestinal Function ◽  
Sample Sizes ◽  
Advantages And Disadvantages ◽  
Function Recovery ◽  
Larger Sample

Objective: The present study aimed to compare the efficacy, and advantages and disadvantages of laparoscopic radical cystectomy + extraperitoneal bilateral ureterocutaneostomy versus laparoscopic radical cystectomy + ileal cystoplasty (Bricker procedure) in the treatment of invasive bladder cancer. Method: Forty-five patients (retrospectively registered) with grade II–III bladder invasive urothelial carcinoma were divided into two groups to compare clinical efficacy, operative duration and blood loss, postoperative intestinal function recovery, length of hospitalization, and complications. Those in the ureterocutaneostomy group (n=25) were treated using laparoscopic radical cystectomy + extraperitoneal bilateral ureterocutaneostomy, while those in the ileal cystoplasty group (n=20) were treated using laparoscopic radical cystectomy + ileal cystoplasty. Results: Laparoscopic radical cystectomy + extraperitoneal bilateral ureterocutaneostomy shortened the operation, improved patient tolerance, and decreased postoperative intestinal function recovery time. However, its long-term clinical efficacy needs further study using larger sample sizes to confirm these results. Conclusion: Results of this study demonstrated that extraperitoneal bilateral ureterocutaneostomy after cystectomy had advantages of less trauma, a shorter learning curve, less surgical bleeding, and quicker postoperative recovery. Although early and mid-term follow-up revealed a slightly higher incidence of hydronephrosis, the severity of complications was not high in most patients. Nevertheless, the long-term clinical efficacy of this procedure needs further study using larger sample sizes.

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