Regression analysis.
概要
作品: | 373 作品在 41 項出版品 41 種語言 |
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書目資訊
Modelling spatial processes : = the identification and analysis of spatial relationships in regression residuals by means of Moran's I /
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Applied linear statistical models : = regression, analysis of variance, and experimental designs /
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Regression diagnostics : = identifying influential data and sources of collinearity /
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Nonparametric regression and generalized linear models : = a roughness penalty approach /
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Regression modeling strategies : = with applications to linear models, logistic regression, and survival analysis /
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Statistical models for the social and behavioural sciences : = multiple regression and limited-dependent variable models /
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Decision trees for business intelligence and data mining : = using SAS Enterprise Miner /
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Modern regression techniques using R : = a practical guide for students and researchers /
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Statistical tools for nonlinear regression = a practical guide with S-PLUS and R examples /
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Extending the linear model with R : = generalized linear, mixed effects and nonparametric regression models /
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A Post-Construction Evaluation of Long-Term Success in Leed-Certified Residential Communities.
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Modern survival analysis in clinical research = Cox regressions versus accelerated failure time models /
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Statistical models for the social and behavioral sciences = multiple regression and limited-dependent variable models /
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Extending the linear model with R : = generalized linear, mixed effects and nonparametric regression models /
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Rank-based methods for shrinkage and selection : = with application to machine learning /
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Regression methods in biostatistics : = linear, logistic, survival, and repeated measures models /
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Regression with social data : = modeling continuous and limited response variables /
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Regression diagnostics : = identifying influential data and sources of collinearity /
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Introduction to linear regression analysis / = Douglas C. Montgomery, Elizabeth A. Peck, G. Geoffrey Vining.
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Statistical tools for nonlinear regression = a practical guide with S-PLUS and R examples /
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Regression Methods in Biostatistics = Linear, Logistic, Survival, and Repeated Measures Models /
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Recent Advances in Linear Models and Related Areas = Essays in Honour of Helge Toutenburg /
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Clinical prediction models = a practical approach to development, validation, and updating /
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Modelling spatial processes = the identification and analysis of spatial relationships in regression residuals by means of Moran's I /
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Statistical modelling and regression structures = festschrift in honour of Ludwig fahrmeir /
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Operationalizing dynamic pricing models = bayesian demand forecasting and customer choice modeling for low cost carriers /
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Regression methods in biostatistics = linear, logistic, survival, and repeated measures models /
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Applications of linear and nonlinear models = fixed effects, random effects, and total least squares /
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Bayesian smoothing and regression for longitudinal, spatial and event history data /
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Methods and applications of linear models : = regression and the analysis of variance /
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Introduction to mediation, moderation, and conditional process analysis : = a regression-based approach /
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Multivariate nonparametric regression and visualization : = with R and applications to finance /
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Beyond multiple linear regression : = applied generalized linear models and multilevel models in R /
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Dissertation on Estimating School Choice Effects Using Centralized School Assignments.
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The GVAR Handbook = Structure and Applications of a Macro Model of the Global Economy for Policy Analysis /
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Regression modeling strategies = with applications to linear models, logistic and ordinal regression, and survival analysis /
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Effective statistical learning methods for actuaries.. II,. Tree-based methods and extensions
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Executive stock options: The effect on discretionary accruals and earnings manipulation.
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Compiler-Assisted Software Fault Tolerance for Bare Metal and RTOS Applications on Embedded Platforms.
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Body Image Flexibility and the Impact of Beauty Ideal Exposure on Unhealthy Exercise amongst College Students.
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Predictors of Perfectionistic Tendencies in Sport among Undergraduate Kinesiology Students.
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Applications of linear and nonlinear models = fixed effects, random effects, and total least squares /
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Applied linear regression for business analytics with R = a practical guide to data science with case studies /
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Bayesian Methods for Large Spatial Data Sets with Materials and Environmental Science Applications.
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Teacher Self-Efficacy and Teacher Work Engagement for Expatriate Teachers at International K12 Schools in China.
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The Relationship between Organizational Culture and Hospital Performance in the Veterans Health Administration.
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Examining the Relationship Between Life Skill Development and Negative Experiences in Sport: The Influence of Resilience.
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Internet of Things (IoT) Anomaly Detection Using Machine Learning Techniques: Parameter Optimization and Algorithm Comparison.
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Predicting Undergraduate Student Dropout Using Artificial Intelligence, Big Data and Machine Learning.
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The Long-Term Effects of Urban Cover Changes on Thermal Environment Using Dense Landsat Time Series.
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Ev Friendly Cities: A Comparison of Policy and Infrastructure in Sixteen Global Cities.
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Parents' Report of Autism: A Correlation of Sociobehavioral Communications and Aberrant Behaviors.
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Determinants of Internal Audit Effectiveness in Public Universities in the South-West Nigeria.
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The Abraham Solvation Model used for Prediction of Solvent-Solute Interactions and New Methods for Updating Parameters.
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Characterizing Early Alzheimer's Disease and Disease Progression Using Noninvasive MRI.
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Functional Brain Connectivity Associated with Repetitive Behavior in Autism Spectrum Disorder.
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Traffic Fatality Rate Prediction Based on Deep Neural Network and Bayesian Neural Network.
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A Study of Contextual Factors in Premature NCD Mortality Reduction in Selected African Countries Within the Sdg Framework.
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Studies on the Use of Machine Learning Algorithms for Analysis and Design of Materials at Multiple Length Scales.
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Classifying Nebulous Activities Cost in Cost Rate Modeling for Aerospace Manufacturing : = A Predictive Correlational Study.
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