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Agent-based Models and Causal Inference

provides a powerful and cogent alternative to standard statistical causal-modeling approaches to causation. Especially valuable is Manzo's careful;

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Handbook of Graphical Models

foundations, computational aspects, statistical inference, causal inference, and applications Balanced coverage of concepts, theory, methods;

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Handbook of Graphical Models

foundations, computational aspects, statistical inference, causal inference, and applications * Balanced coverage of concepts, theory, methods;

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Sense and Nonsense of Statistical Inference: Controversy

epistemology; reveals fallacious practices in statistical causal inference, stressing the misuse of regression models and time-series analysis as;

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Sense and Nonsense of Statistical Inference

epistemology; reveals fallacious practices in statistical causal inference, stressing the misuse of regression models and time-series analysis as;

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Confounding in Causal Inference

complex social phenomena under study, so as to inform causal inferences in the social sciences from statistical linear models.;

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Big Data in Omics and Imaging: Integrated Analysis and Causal Inference

for inferring multilevel omic and image causal networks Present statistical methods and computational algorithms for searching causal;

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Big Data in Omics and Imaging: Integrated Analysis and Causal Inference

various causal models as a general framework for inferring multilevel omic and image causal networks Present statistical methods;

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Statistical Models For Causal Analysis

This volume provides an overview of statistical models commonly used in the causal analyses of non-experimental data in the social and;

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Elements of Causal Inference

A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning. The;

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Introduction to Statistical Decision Theory

Introduction to Statistical Decision Theory: Utility Theory and Causal Analysis provides the theoretical background to approach decision;

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Introduction to Statistical Decision Theory

Introduction to Statistical Decision Theory: Utility Theory and Causal Analysis provides the theoretical background to approach decision;

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Statistical Models & Causal Inference

David A. Freedman presents here a definitive synthesis of his approach to causal inference in the social sciences. He explores the;

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Statistical Models and Causal Inference

David A. Freedman presents here a definitive synthesis of his approach to causal inference in the social sciences. He explores the;

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Extreme Risk Management

field of quantitative finance on its head and generated severe criticism of the statistical models used to manage risk and predict black swan;

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Statistical Rethinking

Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds your knowledge of and confidence in making inferences from;

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Big Data in Omics and Imaging, Two Volume Set

omic and image causal networks Present statistical methods and computational algorithms for searching causal paths;

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Optimal Statistical Inference in Financial Engineering

Until now, few systematic studies of optimal statistical inference for stochastic processes had existed in the financial engineering;

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Targeted Learning in Data Science: Causal Inference for Complex Longitudinal Studies

research interests include statistical methods in genomics, survival analysis, censored data, machine learning, semiparametric models, causal;

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Propensity Score Analysis: Statistical Methods and Applications

Provides readers with a systematic review of the origins, history, and statistical foundations of Propensity Score Analysis (PSA) and;

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Mathematical Foundations of Infinite-Dimensional Statistical Models

This book develops the theory of statistical inference in statistical models with an infinite-dimensional parameter space, including;

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Multimethod Research, Causal Mechanisms, and Case Studies

, Gary Goertz introduces a new integrated approach that unites three corners of a powerful research triad--causal mechanisms, cross-case causal;

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Multimethod Research, Causal Mechanisms, and Case Studies

, Gary Goertz introduces a new integrated approach that unites three corners of a powerful research triad--causal mechanisms, cross-case causal;

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Statistical Inference

A Balanced Treatment of Bayesian and Frequentist Inference Statistical Inference: An Integrated Approach, Second Edition presents an;

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Observation and Experiment An Introduction to Causal Inference

of Statistical Wisdom An excellent introduction...Well-written and thoughtful...from one of causal inference's noted experts. -Journal of the;

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Inferential Models

A New Approach to Sound Statistical Reasoning Inferential Models: Reasoning with Uncertainty introduces the authors' recently;

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Inferential Models

A New Approach to Sound Statistical Reasoning Inferential Models: Reasoning with Uncertainty introduces the authors' recently developed;

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