PAR(1) model analysis: a web-based shiny application for analysing periodic autoregressive models

2022 ◽  
pp. 1-22
Author(s):  
T. Manouchehri ◽  
A. R. Nematollahi
Keyword(s):  
Model Analysis ◽  
Autoregressive Models ◽  
Web Based ◽  
Shiny Application

scholarly journals JMASM 50: A Web-based Shiny Application for Conducting a Two Dependent Samples Maximum Test (R)

2017 ◽  
Vol 16 (2) ◽  
pp. 576-579
Author(s):  
Saverpierre Maggio ◽  
Gokul Bhandari ◽  
Shlomo S. Sawilowsky
Keyword(s):  
Web Based ◽  
Maximum Test ◽  
Dependent Samples ◽  
Shiny Application

scholarly journals ShinyGPAS: Interactive genomic prediction accuracy simulator based on deterministic formulas

2017 ◽  
Author(s):  
Gota Morota
Keyword(s):  
Genomic Prediction ◽  
Prediction Accuracy ◽  
Genetic Factors ◽  
Web Browser ◽  
Web Based ◽  
Factors Influencing ◽  
Scatter Plots ◽  
Potential Factors ◽  
Computationally Intensive ◽  
Shiny Application

AbstractBackgroundDeterministic formulas highlight the relationships among prediction accuracy and potential factors influencing prediction accuracy prior to performing computationally intensive cross-validation. Visualizing such deterministic formulas in an interactive manner may lead to a better understanding of how genetic factors control prediction accuracy.ResultsThe software to simulate deterministic formulas for genomic prediction accuracy was implemented in R and encapsulated as a web-based Shiny application. ShinyGPAS (Shiny Genomic Prediction Accuracy Simulator) simulates various deterministic formulas and delivers dynamic scatter plots of prediction accuracy vs. genetic factors impacting prediction accuracy, while requiring only mouse navigation in a web browser. ShinyGPAS is available at: https://chikudaisei.shinyapps.io/shinygpas/.ConclusionShinyGPAS is a shiny-based interactive genomic prediction accuracy simulator using deterministic formulas. It can be used for interactively exploring potential factors influencing prediction accuracy in genome-enabled prediction, simulating achievable prediction accuracy prior to genotyping individuals, or supporting in-class teaching. ShinyGPAS is open source software and it is hosted online as a freely available web-based resource with an intuitive graphical user interface.

The PBL-Evaluator: a web-based tool for assessment in tutorials

1998 ◽  
Vol 62 (9) ◽  
pp. 671-674
Author(s):  
JF Chaves ◽  
JA Chaves ◽  
MS Lantz
Keyword(s):  
Web Based

Using Popular Mobile Devices in Voice Therapy

2013 ◽  
Vol 23 (3) ◽  
pp. 82-87 ◽  
Author(s):  
Eva van Leer
Keyword(s):  
Exercise Behavior ◽  
Voice Therapy ◽  
Pure Oxygen ◽  
Mobile Platforms ◽  
Self Monitoring ◽  
Web Based ◽  
Motivational Messages ◽  
Related Information ◽  
Health Related ◽  
Tailored Approach

Mobile tools are increasingly available to help individuals monitor their progress toward health behavior goals. Commonly known commercial products for health and fitness self-monitoring include wearable devices such as the Fitbit© and Nike + Pedometer© that work independently or in conjunction with mobile platforms (e.g., smartphones, media players) as well as web-based interfaces. These tools track and graph exercise behavior, provide motivational messages, offer health-related information, and allow users to share their accomplishments via social media. Approximately 2 million software programs or “apps” have been designed for mobile platforms (Pure Oxygen Mobile, 2013), many of which are health-related. The development of mobile health devices and applications is advancing so quickly that the Food and Drug Administration issued a Guidance statement with the purpose of defining mobile medical applications and describing a tailored approach to their regulation.

Web-Based Asthma Management Coming Soon

2008 ◽  
Vol 41 (8) ◽  
pp. 23
Author(s):  
MITCHEL L. ZOLER
Keyword(s):  
Asthma Management ◽  
Web Based

Web-Based STD Tool Makes Screening Accessible

2009 ◽  
Vol 42 (19) ◽  
pp. 27
Author(s):  
BRUCE JANCIN
Keyword(s):  
Web Based

Ultrasonic Reflector Classification with Autoregressive Models

1989 ◽  
Vol 1 (1) ◽  
pp. 235-246
Author(s):  
J. Richard Houghton ◽  
Peitao Shen
Keyword(s):  
Autoregressive Models

Regulation of Experienced and Anticipated Regret for Daily Decisions in Younger and Older Adults in a Swedish One-Week Diary Study

GeroPsych ◽  
2013 ◽  
Vol 26 (4) ◽  
pp. 233-241 ◽  
Author(s):  
Pär Bjälkebring ◽  
Daniel Västfjäll ◽  
Boo Johansson
Keyword(s):  
Older Adults ◽  
Diary Study ◽  
Anticipated Regret ◽  
Younger Adults ◽  
Web Based ◽  
Decision Regret ◽  
Diary Method ◽  
Regulation Strategies

Regret and regret regulation were studied using a weeklong web-based diary method. 108 participants aged 19 to 89 years reported regret for a decision made and a decision to be made. They also reported the extent to which they used strategies to prevent or regulate decision regret. Older adults reported both less experienced and anticipated regret compared to younger adults. The lower level of experienced regret in older adults was mediated by reappraisal of the decision. The lower level of anticipated regret was mediated by delaying the decision, and expecting regret in older adults. It is suggested that the lower level of regret observed in older adults is partly explained by regret prevention and regulation strategies.

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