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Showing 1 to 20 of 646 for “"multiple linear regression"”.

  1. In-situ prediction on sensor networks using distributed multiple linear regression models

    … algorithms suited to autonomous operation and multiple applications. We achieve this through development of new algorithms that enable distributed computation of the pseudo inverse of a matrix on a sensor network, thereby enabling a wide range of prediction methods. We apply these models to …

    mit Repository record for In-situ prediction on sensor networks using distributed multiple linear regression models (opens in a new tab)

  2. Fatigue Life Prediction of Edge-Welded Metal Bellows Using Neural Networks and Multiple Linear Regression

    … respectively.</p> <p>Finally, through the use of multiple linear regression, a statistical analysis was made to develop a model capable of accurate prediction. Applying a natural log transformation to the independent variables of amplitude and energy resulted in a model capable of explaining 95 …

    embry-riddle Repository record for Fatigue Life Prediction of Edge-Welded Metal Bellows Using Neural Networks and Multiple Linear Regression (opens in a new tab)

  3. Quantifying Correlated Variables and Determining Signal Phase Reservice Rate Models from Multiple Linear Regression Using Historical Signal Controller Data

    … the corresponding traffic conditions. Through a regression analysis, the data can confirm engineers' initial assumptions and create a guideline to implement phase reservice in coordinated intersections. A linear regression analysis was conducted to investigate the relationship between reservice …

    unr Repository record for Quantifying Correlated Variables and Determining Signal Phase Reservice Rate Models from Multiple Linear Regression Using Historical Signal Controller Data (opens in a new tab)

  4. Implications of Interactions Among Society, Education and Technology: A Comparison of Multiple Linear Regression and Multilevel Modeling in Mathematics Achievement Analyses

    … Maryland. The first analytic approach, standard multiple linear regression, produced a model in which each of the predictors is statistically significant: student gender, prior math achievement, student performance on school district mathematics benchmark exams, teacher years of experience, and …

    wvu Repository record for Implications of Interactions Among Society, Education and Technology: A Comparison of Multiple Linear Regression and Multilevel Modeling in Mathematics Achievement Analyses (opens in a new tab)

  5. Development of Multiple Linear Regression Model and Rule Based Decision Support System to Improve Supply Chain Management of Road Construction Projects in Disaster Regions

    … to construction materials, legal hitches, multiple challenges of hiring labour force and exponential construction rates due to high risk environment along with multiple other factors. The managers at all tiers are facing challenges of overrunning time and budget of supply chain operations …

    bradford Repository record for Development of Multiple Linear Regression Model and Rule Based Decision Support System to Improve Supply Chain Management of Road Construction Projects in Disaster Regions (opens in a new tab)

  6. Essays on Model Selection Uncertainty and Model Averaging: Computational and Empirical Work with Beta Regression, Multiple Linear Regression with ARMA Innovations, and the Minimum Description Length Principle

    … problematic as model selection routinely admits multiple models which imposes extra uncertainty on all post-selection conclusions. This research emphasized integrated model averaging and selection methods to enhance the characterization and handling of model selection uncertainty. In Chapter 2, …

    ku Repository record for Essays on Model Selection Uncertainty and Model Averaging: Computational and Empirical Work with Beta Regression, Multiple Linear Regression with ARMA Innovations, and the Minimum Description Length Principle (opens in a new tab)

  7. The Use of Regularization to Detect Racial Inequities in Pay Equity Studies: An Empirical Study and Reflections on Regulation Methods

    <p>Since the late 1970s, multiple linear regression has been the preferred method for identifying discrimination in pay. An empirical study on this topic was conducted using quantitative critical methods. A literature review first examined conflicting views on using multiple linear regression in …

    denver Repository record for The Use of Regularization to Detect Racial Inequities in Pay Equity Studies: An Empirical Study and Reflections on Regulation Methods (opens in a new tab)

  8. Factors influencing the white-tailed deer harvest in Virginia, 1947-1967 \

    … deer kill data, 1947 to 1967, were analyzed. Multiple linear regression analysis was used as the deer kill, in general, is still increasing in the counties of Virginia. The data concerning proximity, access, human population, farm size, farmland uses, and the types and acreages of forest …

    vt Repository record for Factors influencing the white-tailed deer harvest in Virginia, 1947-1967 \ (opens in a new tab)

  9. A Review of 'Big Data' Variable Selection Procedures For Use in Predictive Modeling

    … modeling techniques on ‘big data.’ For instance, multiple linear regression models cannot be used on datasets with hundreds of variables. However several techniques are becoming common tools for selective inference as the need for analyzing big data increases. Forward selection and penalized …

    duquesne Repository record for A Review of 'Big Data' Variable Selection Procedures For Use in Predictive Modeling (opens in a new tab)

  10. ADVANCING THE SCIENCE OF HIRING TEACHERS : AN ANALYSIS OF THE EFFECTS OF TEACHER CHARACTERISTICS ON STUDENT ACHIEVEMENT

    … characteristics and student achievement will be multiple linear regression. The research design includes: (a) criteria used for study selection, (b) operational definitions of the constructs being studied, (c) description of instruments used to measure the constructs, (d) the processes used to …

    ecu Repository record for ADVANCING THE SCIENCE OF HIRING TEACHERS : AN ANALYSIS OF THE EFFECTS OF TEACHER CHARACTERISTICS ON STUDENT ACHIEVEMENT (opens in a new tab)

  11. Effect Of Digital Advertising On Website Traffic At A Kentucky Comprehensive Regional University

    … website traffic analytics, this study employed multiple linear regression analysis and time series methods to understand the similarities and differences between key performance indicators of paid traffic and organic traffic as they relate to key performance indicators. Data from Google …

    eku Repository record for Effect Of Digital Advertising On Website Traffic At A Kentucky Comprehensive Regional University (opens in a new tab)

  12. Neural Network Prediction of Math and Reading Proficiency as Reported in the Educational Longitudinal Study 2002 Based on Non-Curricular Variables

    … tool for constructing predictive models is multiple linear regression. This research sought to compare the performance of a three-layer back propagation neural network to that of traditional multiple linear regression in predicting math and reading proficiency from 103 non-curricular …

    duquesne Repository record for Neural Network Prediction of Math and Reading Proficiency as Reported in the Educational Longitudinal Study 2002 Based on Non-Curricular Variables (opens in a new tab)

  13. Low Proof Load Prediction of Ultimate Strengths of Fiberglass/Epoxy I-Beams Using Acoustic Emission

    … (hit) into failure mechanism clusters. Then a multiple linear regression analysis was performed using the percentage of hits associated with each failure mechanism along with the epoxy type to develop a prediction equation. The results of this analysis provided a prediction to within a 36.0% …

    embry-riddle Repository record for Low Proof Load Prediction of Ultimate Strengths of Fiberglass/Epoxy I-Beams Using Acoustic Emission (opens in a new tab)

  14. Impact of Combat Stress on Mental Health Outcomes: BRFSS Survey Data 2006

    … factor in poor mental health outcomes. Methods: Multiple logistic regression (n = 195,048) and multiple linear regression (n = 264,154) were performed on the 2006 Behavioral Risk Factor Surveillance System (BRFSS) survey. Veteran status and a host of demographic and health status questions were …

    vcu Repository record for Impact of Combat Stress on Mental Health Outcomes: BRFSS Survey Data 2006 (opens in a new tab)

  15. Simultaneous confidence bands in linear regression analysis

    … on the plausible range of an<br/>unknown regression model. For a simple linear regression model, the most frequently<br/>quoted bands in the statistical literature include the two-segment band, the three-segment<br/>band and the hyperbolic band, and for a multiple linear regression model, …

    soton Repository record for Simultaneous confidence bands in linear regression analysis (opens in a new tab)

  16. Renogram Image Characteristics and the Reproducibility of Differential Renal Function Measurement

    … and the HRP methods was tested with univariate linear regression. The results of the univariate linear regression were used to plan the multiple linear regression combinations. All possible combinations were tested with multiple linear regression. Results The goodness-to-fit for the multiple

    cape-town Repository record for Renogram Image Characteristics and the Reproducibility of Differential Renal Function Measurement (opens in a new tab)

  17. Role of disaffiliation from fundamentalism and authoritarian religions on mental health

    … wellbeing. Pearson correlations and a multiple linear regression failed to find a significant relationship between each of these variables. It is important to proceed with caution in the treatment of psychological distress when evaluating the role of religious disaffiliation.

    okstate Repository record for Role of disaffiliation from fundamentalism and authoritarian religions on mental health (opens in a new tab)

  18. INFERENCE AFTER VARIABLE SELECTION

    This thesis presents inference for the multiple linear regression model Y = beta_1 x_1 + ... + beta_p x_p + e after model or variable selection, including prediction intervals for a future value of the response variable Y_f, and testing hypotheses with the bootstrap. If n is the sample size, most …

    siu-theses Repository record for INFERENCE AFTER VARIABLE SELECTION (opens in a new tab)

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