scholarly journals The Fence Methods

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Jiming Jiang
Keyword(s):  
Model Selection ◽  
Future Research ◽  
Fence Methods

This paper provides an overview of a recently developed class of strategies for model selection, known as the fence methods. It also offers directions of future research as well as challenging problems.

scholarly journals Fence methods for mixed model selection

2008 ◽  
Vol 36 (4) ◽  
pp. 1669-1692 ◽  
Author(s):  
Jiming Jiang ◽  
J. Sunil Rao ◽  
Zhonghua Gu ◽  
Thuan Nguyen
Keyword(s):  
Model Selection ◽  
Mixed Model ◽  
Fence Methods

scholarly journals Comparison among Akaike Information Criterion, Bayesian Information Criterion and Vuong's test in Model Selection: A Case Study of Violated Speed Regulation in Taiwan

2019 ◽  
Vol 3 (1) ◽  
pp. 293 ◽  
Author(s):  
Kim-Hung Pho ◽  
Sel Ly ◽  
Sal Ly ◽  
T. Martin Lukusa
Keyword(s):  
Model Selection ◽  
Poisson Regression ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Information Criterion ◽  
Future Research ◽  
Data Set ◽  
Research Issues ◽  
Creative Commons ◽  
Advantages And Disadvantages

When doing research on scientific issues, it is very significant if our research issues are closely connected to real applications. In reality, when analyzing data in practice, there are frequently several models that can appropriate to the survey data. Hence, it is necessary to have a standard criterion to choose the most ecient model. In this article, our primary interest is to compare and discuss about the criteria for selecting a model and its applications. The authors provide approaches and procedures of these methods and apply to the traffic violation data where we look for the most appropriate model among Poisson regression, Zero-inflated Poisson regression and Negative binomial regression to capture between number of violated speed regulations and some factors including distance covered, motorcycle engine and age of respondents by using AIC, BIC and Vuong's test. Based on results on the training, validation and test data set, we find that the criteria AIC and BIC are more consistent and robust performance in model selection than the Vuong's test. In the present paper, the authors also discuss about advantages and disadvantages of these methods and provide some of the suggestions with potential directions in future research. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.

scholarly journals Beyond Lasso: A Survey of Nonconvex Regularization in Gaussian Graphical Models

2020 ◽  
Author(s):  
Donald Ray Williams
Keyword(s):  
Model Selection ◽  
Graphical Models ◽  
Graphical Model ◽  
Tuning Parameter ◽  
Future Research ◽  
Dependence Structure ◽  
Post Traumatic Stress ◽  
Absolute Deviation ◽  
Oracle Properties ◽  
Nonconvex Regularization

Studying complex relations in multivariate datasets is a common task in psychological science. Recently, the Gaussian graphical model has emerged as an increasingly popular model for characterizing the conditional dependence structure of random variables. Although the graphical lasso ($\ell_1$-regularization) is the most well-known estimator across the sciences, it has several drawbacks that make it less than ideal for model selection. There are now alternative forms of regularization that were developed specifically to overcome issues inherent to the $\ell_1$-penalty.To date, this information has not been synthesized. This paper provides a comprehensive survey of nonconvex regularization that spans from the smoothly clipped absolute deviation penalty to continuous approximations of the $\ell_0$-penalty (i.e., best subset) for directly estimating the inverse covariance matrix. A common thread shared by these penalties is that they all enjoy the oracle properties, that is, they perform as though the \emph{true} generating model were known in advance. To ensure their theoretical properties are general, I conducted extensive numerical experiments that indicated superior and more than competitive performance when compared to glasso and non-regularized model selection, respectively, all the while being computationally feasible for many variables. In addition, the important topics of tuning parameter selection and statistical inference in regularized models are reviewed.The penalties are employed to estimate the dependence structure of post-traumatic stress disorder symptoms. The discussion includes several ideas for future research, including a plethora of information to facilitate their study. I have implemented the methods in the

Selection and industrial applications of panel data based demand forecasting models

2016 ◽  
Vol 116 (6) ◽  
pp. 1131-1159
Author(s):  
Shuyun Ren ◽  
Tsan-Ming Choi
Keyword(s):  
Panel Data ◽  
Model Selection ◽  
Demand Forecasting ◽  
Industrial Applications ◽  
Data Models ◽  
Future Research ◽  
Panel Data Models ◽  
Content Type ◽  
Forecasting Models ◽  
The Right

Purpose – Panel data-based demand forecasting models have been widely adopted in various industrial settings over the past few decades. Despite being a highly versatile and intuitive method, in the literature, there is a lack of comprehensive review examining the strengths, the weaknesses, and the industrial applications of panel data-based demand forecasting models. The purpose of this paper is to fill this gap by reviewing and exploring the features of various main stream panel data-based demand forecasting models. A novel process, in the form of a flowchart, which helps practitioners to select the right panel data models for real world industrial applications, is developed. Future research directions are proposed and discussed. Design/methodology/approach – It is a review paper. A systematically searched and carefully selected number of panel data-based forecasting models are examined analytically. Their features are also explored and revealed. Findings – This paper is the first one which reviews the analytical panel data models specifically for demand forecasting applications. A novel model selection process is developed to assist decision makers to select the right panel data models for their specific demand forecasting tasks. The strengths, weaknesses, and industrial applications of different panel data-based demand forecasting models are found. Future research agenda is proposed. Research limitations/implications – This review covers most commonly used and important panel data-based models for demand forecasting. However, some hybrid models, which combine the panel data-based models with other models, are not covered. Practical implications – The reviewed panel data-based demand forecasting models are applicable in the real world. The proposed model selection flowchart is implementable in practice and it helps practitioners to select the right panel data-based models for the respective industrial applications. Originality/value – This paper is the first one which reviews the analytical panel data models specifically for demand forecasting applications. It is original.

Parasite defense mechanisms in bees: behavior, immunity, antimicrobials, and symbionts

2019 ◽  
Vol 4 (1) ◽  
pp. 59-76 ◽  
Author(s):  
Alison E. Fowler ◽  
Rebecca E. Irwin ◽  
Lynn S. Adler
Keyword(s):  
Defense Mechanisms ◽  
Poor Quality ◽  
Future Research ◽  
Immune Priming ◽  
Social Bees ◽  
Bee Health ◽  
Landscape Scales ◽  
And Function ◽  
Solitary Species

Parasites are linked to the decline of some bee populations; thus, understanding defense mechanisms has important implications for bee health. Recent advances have improved our understanding of factors mediating bee health ranging from molecular to landscape scales, but often as disparate literatures. Here, we bring together these fields and summarize our current understanding of bee defense mechanisms including immunity, immunization, and transgenerational immune priming in social and solitary species. Additionally, the characterization of microbial diversity and function in some bee taxa has shed light on the importance of microbes for bee health, but we lack information that links microbial communities to parasite infection in most bee species. Studies are beginning to identify how bee defense mechanisms are affected by stressors such as poor-quality diets and pesticides, but further research on this topic is needed. We discuss how integrating research on host traits, microbial partners, and nutrition, as well as improving our knowledge base on wild and semi-social bees, will help inform future research, conservation efforts, and management.

Dicarbonyl derived post-translational modifications: chemistry bridging biology and aging-related disease

2020 ◽  
Vol 64 (1) ◽  
pp. 97-110
Author(s):  
Christian Sibbersen ◽  
Mogens Johannsen
Keyword(s):  
Mass Spectrometry ◽  
Future Research ◽  
Amino Acid Residues ◽  
Post Translational Modification ◽  
Dicarbonyl Compounds ◽  
Protein Targets ◽  
Post Translational Modifications ◽  
Reactive Protein ◽  
Glycation End Products ◽  
Direct Mass Spectrometry

Abstract In living systems, nucleophilic amino acid residues are prone to non-enzymatic post-translational modification by electrophiles. α-Dicarbonyl compounds are a special type of electrophiles that can react irreversibly with lysine, arginine, and cysteine residues via complex mechanisms to form post-translational modifications known as advanced glycation end-products (AGEs). Glyoxal, methylglyoxal, and 3-deoxyglucosone are the major endogenous dicarbonyls, with methylglyoxal being the most well-studied. There are several routes that lead to the formation of dicarbonyl compounds, most originating from glucose and glucose metabolism, such as the non-enzymatic decomposition of glycolytic intermediates and fructosyl amines. Although dicarbonyls are removed continuously mainly via the glyoxalase system, several conditions lead to an increase in dicarbonyl concentration and thereby AGE formation. AGEs have been implicated in diabetes and aging-related diseases, and for this reason the elucidation of their structure as well as protein targets is of great interest. Though the dicarbonyls and reactive protein side chains are of relatively simple nature, the structures of the adducts as well as their mechanism of formation are not that trivial. Furthermore, detection of sites of modification can be demanding and current best practices rely on either direct mass spectrometry or various methods of enrichment based on antibodies or click chemistry followed by mass spectrometry. Future research into the structure of these adducts and protein targets of dicarbonyl compounds may improve the understanding of how the mechanisms of diabetes and aging-related physiological damage occur.

Effect of Teacher Training Sessions on Listener Perception of Voice Disorders

1985 ◽  
Vol 16 (1) ◽  
pp. 25-28 ◽  
Author(s):  
Nicholas J. DeGregorio ◽  
Nancy Gross Polow
Keyword(s):  
Teacher Training ◽  
School System ◽  
Voice Disorders ◽  
Future Research ◽  
Speech Language Pathologists ◽  
Speech Language Pathologist ◽  
Bergen County ◽  
Experimental Group

The present study was designed to investigate the effect of teacher training sessions on listener perception of voice disorders. Three ASHA certified speech-language pathologists provided the criteria mean. Thirty randomly selected teachers from a Bergen County school system, randomly placed into two groups, served as subjects. The experimental group received three training sessions on consecutive weeks. Three weeks after the end of training, both groups were given a posttest. Listener perception scores were significantly higher for the experimental group. The implications of these results for in-service workshops, teacher/speech-language pathologist interaction and future research are discussed.

Comparative Effects of High-Tech Visual Scene Displays and Low-Tech Isolated Picture Symbols on Engagement From Students With Multiple Disabilities

2019 ◽  
Vol 50 (4) ◽  
pp. 693-702 ◽  
Author(s):  
Christine Holyfield ◽  
Sydney Brooks ◽  
Allison Schluterman
Keyword(s):  
Language Learning ◽  
Augmentative And Alternative Communication ◽  
Visual Analysis ◽  
Multiple Disabilities ◽  
Visual Scene ◽  
Future Research ◽  
High Tech ◽  
Single Subject ◽  
Wide Range ◽  
The Difference

Purpose Augmentative and alternative communication (AAC) is an intervention approach that can promote communication and language in children with multiple disabilities who are beginning communicators. While a wide range of AAC technologies are available, little is known about the comparative effects of specific technology options. Given that engagement can be low for beginning communicators with multiple disabilities, the current study provides initial information about the comparative effects of 2 AAC technology options—high-tech visual scene displays (VSDs) and low-tech isolated picture symbols—on engagement. Method Three elementary-age beginning communicators with multiple disabilities participated. The study used a single-subject, alternating treatment design with each technology serving as a condition. Participants interacted with their school speech-language pathologists using each of the 2 technologies across 5 sessions in a block randomized order. Results According to visual analysis and nonoverlap of all pairs calculations, all 3 participants demonstrated more engagement with the high-tech VSDs than the low-tech isolated picture symbols as measured by their seconds of gaze toward each technology option. Despite the difference in engagement observed, there was no clear difference across the 2 conditions in engagement toward the communication partner or use of the AAC. Conclusions Clinicians can consider measuring engagement when evaluating AAC technology options for children with multiple disabilities and should consider evaluating high-tech VSDs as 1 technology option for them. Future research must explore the extent to which differences in engagement to particular AAC technologies result in differences in communication and language learning over time as might be expected.

Self-Compassion and Quality of Life in Adults Who Stutter

2020 ◽  
Vol 29 (4) ◽  
pp. 2097-2108
Author(s):  
Robyn L. Croft ◽  
Courtney T. Byrd
Keyword(s):  
Quality Of Life ◽  
Social Connectedness ◽  
The Self ◽  
Future Research ◽  
Self Compassion ◽  
Adults Who Stutter ◽  
And Gender ◽  
Relationship Of ◽  
The Impact

Purpose The purpose of this study was to identify levels of self-compassion in adults who do and do not stutter and to determine whether self-compassion predicts the impact of stuttering on quality of life in adults who stutter. Method Participants included 140 adults who do and do not stutter matched for age and gender. All participants completed the Self-Compassion Scale. Adults who stutter also completed the Overall Assessment of the Speaker's Experience of Stuttering. Data were analyzed for self-compassion differences between and within adults who do and do not stutter and to predict self-compassion on quality of life in adults who stutter. Results Adults who do and do not stutter exhibited no significant differences in total self-compassion, regardless of participant gender. A simple linear regression of the total self-compassion score and total Overall Assessment of the Speaker's Experience of Stuttering score showed a significant, negative linear relationship of self-compassion predicting the impact of stuttering on quality of life. Conclusions Data suggest that higher levels of self-kindness, mindfulness, and social connectedness (i.e., self-compassion) are related to reduced negative reactions to stuttering, an increased participation in daily communication situations, and an improved overall quality of life. Future research should replicate current findings and identify moderators of the self-compassion–quality of life relationship.

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