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Probability & Statistics - Regression Analysis

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Predictive Analytics Using Statistics and Big Data: Concepts and Modeling
by Pandey, Arvind    Rajput, Dharmendra Singh    Mohbey, Krishna Kumar
(Paperback - English - 9789811490507)
This book presents a selection of the latest and representative developments in predictive analytics using big data technologies. It focuses on some critical aspects of big data and machine learning and provides studies for readers. The chapters address a comprehensive range of advanced data technologies used for statistical modeling towards predictive analytics.Topics included in this book include: - Categorized machine learning algorithms- Player monopoly in cricket teams.- Chain type estimators- Log type estimators- Bivariate survival data using shared inverse Gaussian frailty models- Weblog analysis- COVID-19 epidemiologyThis reference book will be of signif ..
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Rp. 866.000
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Rp. 1.019.000
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Linear Regression Models: Applications in R
by Hoffmann, John P.       
(Paperback - English - 9780367753665)
Research in social and behavioral sciences has benefited from linear regression models (LRMs) for decades to identify and understand the associations among a set of explanatory variables and an outcome variable. Linear Regression Models: Applications in R provides you with a comprehensive treatment of these models and indispensable guidance about how to estimate them using the R software environment. After furnishing some background material, the author explains how to estimate simple and multiple LRMs in R, including how to interpret their coefficients and understand their assumptions. Several chapters thoroughly describe these assumptions and explain how to d ..
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Rp. 1.943.000
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Rp. 2.285.000
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Surrogates: Gaussian Process Modeling, Design, and Optimization for the Applied Sciences
by Gramacy, Robert B.       
(Paperback - English - 9781032242552)
Surrogates: a graduate textbook, or professional handbook, on topics at the interface between machine learning, spatial statistics, computer simulation, meta-modeling (i.e., emulation), design of experiments, and optimization. Experimentation through simulation, "human out-of-the-loop" statistical support (focusing on the science), management of dynamic processes, online and real-time analysis, automation, and practical application are at the forefront. Topics include: ul li Gaussian process (GP) regression for flexible nonparametric and nonlinear modeling. li li Applications to uncertainty quantification, sensitivity analysis, calibration of computer m ..
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Rp. 1.402.000
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Rp. 1.649.000
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DATA MINING and MACHINE LEARNING. PREDICTIVE TECHNIQUES: REGRESSION, GENERALIZED LINEAR MODELS, SUPPORT VECTOR MACHINE and NEURAL NETWORKS: Examples w
by Pérez López, César       
(Paperback - English - 9781794829466)
Data Mining and Machine Learning uses two types of techniques: predictive techniques (supervised techniques), which trains a model on known input and output data so that it can predict future outputs, and descriptive techniques (unsupervised techniques), which finds hidden patterns or intrinsic structures in input data. The aim of predictive techniques is to build a model that makes predictions based on evidence in the presence of uncertainty. A predictive algorithm takes a known set of input data and known responses to the data (output) and trains a model to generate reasonable predictions for the response to new data. Predictive techniques uses regression tech ..
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Rp. 678.000
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Rp. 797.000
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Linear Regression Models: Applications in R
by Hoffmann, John P.       
(Hardcover - English - 9780367753689)
Research in social and behavioral sciences has benefited from linear regression models (LRMs) for decades to identify and understand the associations among a set of explanatory variables and an outcome variable. Linear Regression Models: Applications in R provides you with a comprehensive treatment of these models and indispensable guidance about how to estimate them using the R software environment. After furnishing some background material, the author explains how to estimate simple and multiple LRMs in R, including how to interpret their coefficients and understand their assumptions. Several chapters thoroughly describe these assumptions and explain how to d ..
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Rp. 4.706.000
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Rp. 5.534.000
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Spatial Predictive Modeling with R
by Li, Jin       
(Hardcover - English - 9780367550547)
Spatial predictive modeling (SPM) is an emerging discipline in applied sciences, playing a key role in the generation of spatial predictions in various disciplines. SPM refers to preparing relevant data, developing optimal predictive models based on point data, and then generating spatial predictions. This book aims to systematically introduce the entire process of SPM as a discipline. The process contains data acquisition, spatial predictive methods and variable selection, parameter optimization, accuracy assessment, and the generation and visualization of spatial predictions, where spatial predictive methods are from geostatistics, modern statistics, and machi ..
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Rp. 3.144.000
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Rp. 3.697.000
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Advanced Statistics for Physical and Occupational Therapy
by Almonroeder, Thomas Gus       
(Hardcover - English - 9781032017129)
Advanced Statistics for Physical and Occupational Therapy explains the basis for statistical analyses that are commonly used to answer clinical research questions related to physical and occupational therapy. This textbook provides a resource to help students and faculty in physical and occupational therapy graduate programs understand the basis for common statistical analyses and be able to apply these techniques in their own research. This textbook provides readers with the basis for common statistical analyses, including t -tests, analysis of variance, regression, and nonparametric tests. Each chapter includes step-by-step tutorials with corresponding exampl ..
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Rp. 4.426.000
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The Python Guide for New Data Scientists
by Strickland, Jeffrey       
(Hardcover - English - 9781458321619)
The Python Guide for New Data Scientists is written for someone who has graduated from college and has either had some discipline related course or has a desire to learn some of the basic data science building blocks. Data science is interdisciplinary, andhave work with people who have backgrounds in business or economics and are competent data scientists with some additional coursework. Ordinarily, we look for potential data scientists who have degrees in statistics, computer science, econometrics, information technology, operations research, mathematics, or engineering. That encompasses a wide range of disciplines. People who become data scientists generally h ..
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Rp. 1.779.000
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Rp. 2.092.000
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Anova and Mixed Models: A Short Introduction Using R
by Meier, Lukas       
(Paperback - English - 9780367704209)
strong ANOVA and Mixed Models: A Short Introduction Using R strong provides both the practitioner and researcher a compact introduction to the analysis of data from the most popular experimental designs. Based on knowledge from an introductory course on probability and statistics, the theoretical foundations of the most important models are introduced. The focus is on an intuitive understanding of the theory, common pitfalls in practice, and the application of the methods in R. From data visualization and model fitting, up to the interpretation of the corresponding output, the whole workflow is presented using R. The book does not only cover standard ANOVA m ..
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Rp. 1.581.000
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Rp. 1.860.000
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Anova and Mixed Models: A Short Introduction Using R
by Meier, Lukas       
(Hardcover - English - 9780367704223)
strong ANOVA and Mixed Models: A Short Introduction Using R strong provides both the practitioner and researcher a compact introduction to the analysis of data from the most popular experimental designs. Based on knowledge from an introductory course on probability and statistics, the theoretical foundations of the most important models are introduced. The focus is on an intuitive understanding of the theory, common pitfalls in practice, and the application of the methods in R. From data visualization and model fitting, up to the interpretation of the corresponding output, the whole workflow is presented using R. The book does not only cover standard ANOVA m ..
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Rp. 3.958.000
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Rp. 4.654.000
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Fundamentals of Mathematical Statistics
by Lauritzen, Steffen       
(Hardcover - English - 9781032223827)
strong Fundamentals of Mathematical Statistics strong is meant for a standard one-semester advanced undergraduate or graduate level course on Mathematical Statistics. It covers all the key topics - statistical models, linear normal models, exponential families, estimation, asymptotics of maximum likelihood, significance testing, and models for tables of counts. It assumes a good background in mathematical analysis, linear algebra, and probability, but includes an appendix with basic results from these areas. Throughout the text, there are numerous examples and graduated exercises that illustrate the topics covered, rendering the book suitable for teaching or ..
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HARGA DISKON 8-10 FEB 2023
Rp. 2.318.000
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Rp. 2.725.000
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Applied Categorical and Count Data Analysis
by Tang, Wan    He, Hua    Tu, Xin M.
(Hardcover - English - 9780367568276)
Developed from the authors' graduate-level biostatistics course, Applied Categorical and Count Data Analysis, Second Edition explains how to perform the statistical analysis of discrete data, including categorical and count outcomes. The authors have been teaching categorical data analysis courses at the University of Rochester and Tulane University for more than a decade. This book embodies their decade-long experience and insight in teaching and applying statistical models for categorical and count data. The authors describe the basic ideas underlying each concept, model, and approach to give readers a good grasp of the fundamentals of the methodology without ..
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Rp. 2.318.000
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Rp. 2.725.000
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Model-Based Clustering, Classification, and Density Estimation Using McLust in R
by Scrucca, Luca    Fraley, Chris    Murphy, T. Brendan
(Paperback - English - 9781032234953)
Model-based clustering and classification methods provide a systematic statistical approach to clustering, classification, and density estimation via mixture modeling. The model-based framework allows the problems of choosing or developing methods to be understood within the context of statistical modeling. The mclust package for the statistical environment R is a widely-adopted platform implementing these model-based strategies. The package includes both summary and visual functionality, complementing procedures for estimating and choosing models. Key features of the book: ul li An introduction to the model-based approach and the mclust R package li l ..
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Rp. 1.580.000
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Rp. 1.858.000
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Model-Based Clustering, Classification, and Density Estimation Using McLust in R
by Scrucca, Luca    Fraley, Chris    Murphy, T. Brendan
(Hardcover - English - 9781032234960)
Model-based clustering and classification methods provide a systematic statistical approach to clustering, classification, and density estimation via mixture modeling. The model-based framework allows the problems of choosing or developing methods to be understood within the context of statistical modeling. The mclust package for the statistical environment R is a widely-adopted platform implementing these model-based strategies. The package includes both summary and visual functionality, complementing procedures for estimating and choosing models. Key features of the book: ul li An introduction to the model-based approach and the mclust R package li l ..
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Buku Pre-Order biasanya terkirim 8-14 hari kerja setelah Publication Date. Tidak bisa menggabungkan buku ini dengan buku lain dalam satu order. Buku dikirim kurir lokal dengan nomor lacak
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Rp. 4.045.000
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Rp. 4.757.000
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Advanced R Solutions
by Grosser, Malte    Bumann, Henning    Wickham, Hadley
(Hardcover - English - 9781032007502)
This book offers solutions to all 284 exercises in Advanced R, Second Edition . All the solutions have been carefully documented and made to be as clear and accessible as possible. Working through the exercises and their solutions will give you a deeper understanding of a variety of programming challenges, many of which are relevant to everyday work. This will expand your set of tools on a technical and conceptual level. You will be able to transfer many of the specific programming schemes directly and will discover far more elegant solutions to everyday problems. Features: ul li When R creates copies, and how it affects memory usage and code performa ..
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PREDICTIVE ANALYTICS with NEURAL NETWORKS using MATLAB
by Perez Lopez, Cesar       
(Paperback - English - 9781716601569)
Predictive analytics encompasses a variety of statistical techniques from predictive modeling, machine learning, and data mining that analyze current and historical facts to make predictions about future or otherwise unknown events. Different work fields with neural networks and predictive analytics techniques are listed below: The multilayer perceptron (MLP), A radial basis function (RBF), Support vector machines (SVM), Fit regression models with neural networks, Time series neural networks, Hopfield and linear neural networks, Generalized regression and LVQ neural networks, Adaptative linear filters and non linear problems ..
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Rp. 682.000
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Rp. 802.000
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Nonlinear Regression P
by Seber    Wild   
(Paperback - English - 9780471471356)
WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. From the Reviews of Nonlinear Regression "A very good book and an important one in that it is likely to become a standard reference for all interested in nonlinear regression; andwould imagine that any statistician concerned with nonlinear regression would want a ..
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Rp. 3.646.000
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Rp. 4.287.000
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Linear Regression Analysis 2e
by Seber    Lee   
(Hardcover - English - 9780471415404)
Concise, mathematically clear, and comprehensive treatment of the subject. br * Expanded coverage of diagnostics and methods of model fitting. br * Requires no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis of variance models. br * More than 200 problems throughout the book plus outline solutions for the exercises. br * This revision has been extensively class-tested. ..
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Rp. 4.208.000
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Rp. 4.948.000
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Applied Logistic Regression: Solutions Manual
by Hosmer, David W.    Lemeshow, Stanley   
(Paperback - English - 9780471208266)
Presenting information on logistic regression models, this work explains difficult concepts through illustrative examples. This is a solutions manual to accompany applied Logistic Regression, 2nd Edition. ..
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Logistic Regression Models
by Hilbe, Joseph M.       
(Hardcover - English - 9781420075755)
strong Logistic Regression Models strong presents an overview of the full range of logistic models, including binary, proportional, ordered, partially ordered, and unordered categorical response regression procedures. Other topics discussed include panel, survey, skewed, penalized, and exact logistic models. The text illustrates how to apply the various models to health, environmental, physical, and social science data. Examples illustrate successful modeling br The text first provides basic terminology and concepts, before explaining the foremost methods of estimation (maximum likelihood and IRLS) appropriate for logistic models. It then presents an in-dep ..
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