Second Brain

Tag: source/ingested

679 items with this tag.

Sep 23, 2026
Index: Flows and Crowds
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Sep 23, 2026
Index: Marketing
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Sep 23, 2026
Index: Markets and Finance
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Sep 23, 2026
Index: Organizations
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Sep 23, 2026
Index: Risk
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Sep 23, 2026
Index: Applications
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Sep 23, 2026
Index: Calibration Methods
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Sep 23, 2026
Index: Experimental Design
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Sep 23, 2026
Index: Sensitivity Analysis
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Sep 23, 2026
Index: Validation
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Sep 23, 2026
Index: Calibration and Validation
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Sep 23, 2026
Index: CUBES Model
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Sep 23, 2026
Index: Karakaya Model
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Sep 23, 2026
Index: Consumer Behavior
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Sep 23, 2026
Index: Core Concepts
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Sep 23, 2026
Index: Modeling Approaches
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Sep 23, 2026
Index: Foundations
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Sep 23, 2026
Generative Agents Architecture - Memory, Reflection and Planning
Sep 23, 2026
Validity, Bias and Calibration of LLM-Simulated Populations
Sep 23, 2026
LLM-Powered Agents - Index
Sep 23, 2026
Index: Market Dynamics
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Sep 23, 2026
Index: Networks and Diffusion
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Sep 23, 2026
Index: Word of Mouth
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Sep 23, 2026
Index: Social Dynamics
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Sep 23, 2026
Index: Agent-Based Modeling
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Sep 23, 2026
Index: Foundations (Bayesian Experimental Design)
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Sep 23, 2026
Index: Gradient-Based Unified BOED
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Sep 23, 2026
Index: Modern BED Review
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Sep 23, 2026
Index: Multi-Armed Bandits and Thompson Sampling (Bayesian Experimental Design)
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Sep 23, 2026
Index: Variational EIG Estimators
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Sep 23, 2026
Index: Bayesian Experimental Design
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Sep 23, 2026
Confirmatory Factor Analysis and Structural Equation Models
Sep 23, 2026
Bayesian Copula Estimation
Sep 23, 2026
Factor Analysis and Probabilistic PCA
Sep 23, 2026
Hilbert Space Gaussian Processes (HSGPs)
Sep 23, 2026
Bayesian Non-parametric Causal Inference
Sep 23, 2026
Social Network Models
Sep 23, 2026
Spatial Models — Besag-York-Mollie (BYM)
Sep 23, 2026
Index: Advanced Models
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Sep 23, 2026
Index: Bayesian Causal Inference Methods
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Sep 23, 2026
Index: Dynamic Treatment Regimes
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Sep 23, 2026
Index: Causal Inference Foundations
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Sep 23, 2026
LLM Expert Elicitation for Bayesian Networks
Sep 23, 2026
LLM-BN Decision Support Application
Sep 23, 2026
Shaposhnyk 2025 - Overview
Sep 23, 2026
Index: Knowledge Elicitation for Causal Models
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Sep 23, 2026
Index: Sensitivity Analysis and Complex Mechanisms
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Sep 23, 2026
Index: State-Space and Kalman Filter
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Sep 23, 2026
Index: Time Series Causal Inference
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Sep 23, 2026
Index: Treatment Effect Estimation
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Sep 23, 2026
Index: Bayesian Causal Inference
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Sep 23, 2026
Efficient MCMC
Sep 23, 2026
HMC and Stan in Practice
Sep 23, 2026
Neural Simulation-Based Inference - Overview
Sep 23, 2026
Neural Simulation-Based Inference - Index
Sep 23, 2026
Variational Inference - Index
Sep 23, 2026
Index: Computation
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Sep 23, 2026
Empirical Bayes - Index
Sep 23, 2026
Index: Inference Fundamentals
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Sep 23, 2026
Index: Model Assessment
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Sep 23, 2026
Counterfactual Inference
Sep 23, 2026
Hierarchical Linear Models
Sep 23, 2026
Missing Data — Statistical Rethinking (Lecture 18)
Sep 23, 2026
Bayesian Moderation Analysis
Sep 23, 2026
Shrinkage Priors — Index
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Sep 23, 2026
Index: Regression Models
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Sep 23, 2026
Synthetic Likelihood Construction
Sep 23, 2026
Index: Synthetic Likelihood
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Sep 23, 2026
Index: Appendices
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Sep 23, 2026
Bayesian Workflow - Overview
Sep 23, 2026
Index: Building Models
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Sep 23, 2026
Index: Case Studies
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Sep 23, 2026
Choosing and Building Models
Sep 23, 2026
Computational Troubleshooting
Sep 23, 2026
Index: Computational Workflow
- type/index
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Sep 23, 2026
Evaluating Fitted Models
Sep 23, 2026
Index: Evaluating and Comparing
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Sep 23, 2026
Fitting and Validating Computation
Sep 23, 2026
Index: Foundations
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Sep 23, 2026
Iterative Model Improvement
Sep 23, 2026
Modeling as Software Development
Sep 23, 2026
Index: Simulation-Based Calibration
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Sep 23, 2026
Index: Bayesian Workflow
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Sep 23, 2026
Index: Bayesian Statistics
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Sep 23, 2026
Index: Adjunctions
Sep 23, 2026
Basic Category Theory - Overview
Sep 23, 2026
Index: Foundations
Sep 23, 2026
Index: Limits and Colimits
Sep 23, 2026
Adjunctions Induce Monads
Sep 23, 2026
Algebras for a Monad - Eilenberg-Moore and Kleisli
Sep 23, 2026
Beck's Monadicity Theorem
Sep 23, 2026
Monads - Overview
Sep 23, 2026
Monads and the Monad Laws
Sep 23, 2026
Monads and their Algebras — Index
Sep 23, 2026
Index: Representables
Sep 23, 2026
Index: Synthesis
Sep 23, 2026
Index: Universal Properties
Sep 23, 2026
Index: Category Theory
Sep 23, 2026
Constraint and Score-Based Discovery
Sep 23, 2026
Index: Causal Discovery
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Sep 23, 2026
Asymptotic Normality and Inference for Forests
Sep 23, 2026
Causal Machine Learning - Overview
Sep 23, 2026
Causal Machine Learning - Index
Sep 23, 2026
Index: Vine Copulas
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Sep 23, 2026
Index: Dependence Modeling
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Sep 23, 2026
Index: Difference-in-Differences
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Sep 23, 2026
BLP Demand Estimation - Index
Sep 23, 2026
Dependence Measures for Copulas
Sep 23, 2026
SMM Copula Asymptotic Theory
Sep 23, 2026
SMM Copula Simulation and Application
Sep 23, 2026
SMM Copula Specification Testing
Sep 23, 2026
SMM Estimator for Copulas
Sep 23, 2026
Index: Copula SMM
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Sep 23, 2026
Discrete Choice Models
Sep 23, 2026
Efficient Method of Moments
Sep 23, 2026
Indirect Inference
Sep 23, 2026
Method of Simulated Moments
Sep 23, 2026
Practical Issues in Simulation Estimation
Sep 23, 2026
Simulation-Based Estimation - Overview
Sep 23, 2026
Index: Simulation-Based Estimation
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Sep 23, 2026
Index: Extensions
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Sep 23, 2026
Randomization Inference - Index
Sep 23, 2026
The Experimental Ideal
Sep 23, 2026
Index: Foundations
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Sep 23, 2026
Bayesian Difference in Differences
Sep 23, 2026
Propensity Score Matching - Index
Sep 23, 2026
Synthetic Difference-in-Differences - Index
Sep 23, 2026
Index: Identification Strategies
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Sep 23, 2026
Quasi-Bayes for Plausible Moment Restrictions
Sep 23, 2026
Index: Plausible GMM
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Sep 23, 2026
Index: Regression Foundations
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Sep 23, 2026
Index: Econometrics
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Sep 23, 2026
Conformal Prediction - Index
Sep 23, 2026
Chain-of-Thought Prompting
Sep 23, 2026
Evaluating LLM Systems - Benchmarks, Hallucination and Human Preference
Sep 23, 2026
LLM Reasoning, Retrieval and Agents - Overview
Sep 23, 2026
RLHF and Instruction Tuning
Sep 23, 2026
ReAct - Reasoning and Acting Agents
Sep 23, 2026
Retrieval-Augmented Generation (RAG)
Sep 23, 2026
Reward Modeling from Human Preferences
Sep 23, 2026
Tool Use and the Agent Loop
Sep 23, 2026
LLM Reasoning, Retrieval and Agents - Index
Sep 23, 2026
Probabilistic Forecasting - Index
Sep 23, 2026
Transformers and LLM Foundations - Index
Sep 23, 2026
Bayesian Estimation and Priors for MMM
Sep 23, 2026
Bayesian Media Mix Modeling - Overview
Sep 23, 2026
Carryover (Adstock) Functional Forms
Sep 23, 2026
MMM Model Selection and Application
Sep 23, 2026
ROAS, mROAS, and Optimal Media Mix
Sep 23, 2026
Shape (Saturation) Effects
Sep 23, 2026
Index: Bayesian Media Mix Modeling
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Sep 23, 2026
Bayesian and Hierarchical Extensions of CLV Models
Sep 23, 2026
Customer Lifetime Value - Index
Sep 23, 2026
Index: Geo-Experiment Methodology
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Sep 23, 2026
Response Models for Marketing Management
Sep 23, 2026
The Unfavorable Economics of Ad Experiments - Power and Signal-to-Noise
Sep 23, 2026
User-Level Ad Experiments - Index
Sep 23, 2026
Index: Physics / Foundations
Sep 23, 2026
Index: Physics / Quantum Field Theory
Sep 23, 2026
Index: Physics
Sep 23, 2026
Index: Differential Equations (Probabilistic Numerics)
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Sep 23, 2026
Index: Foundations (Probabilistic Numerics)
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Sep 23, 2026
Index: Integration (Probabilistic Numerics)
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Sep 23, 2026
Index: Linear Algebra (Probabilistic Numerics)
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Sep 23, 2026
Index: Optimisation (Probabilistic Numerics)
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Sep 23, 2026
Probabilistic Numerics - Overview
Sep 23, 2026
Index: Probabilistic Numerics
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Sep 23, 2026
Index: Delayed and Censored Feedback
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Sep 23, 2026
Multiple Testing Corrections
Sep 23, 2026
CUPED and Regression-Adjusted Variance Reduction
Sep 23, 2026
Online Experimentation - Overview
Sep 23, 2026
The Peeking Problem and Optional Stopping
Sep 23, 2026
Online Experimentation - Index
Sep 23, 2026
Survival Analysis
Sep 23, 2026
Index: Experimental Design
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Sep 23, 2026
Index: Pre-registration and Open Science
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Sep 23, 2026
Index: Research Methodology
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Sep 23, 2026
Index: Research
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Sep 18, 2026
ABM Calibration Case Studies
Sep 18, 2026
ABM Calibration Overview
Sep 18, 2026
Approximate Bayesian Computation for ABMs
Sep 18, 2026
GA Fitness Evaluation and the RAM
Sep 18, 2026
Genetic Algorithm Calibration for ABM
Sep 18, 2026
HM-ABC Calibration Framework
Sep 18, 2026
History Matching for ABMs
Sep 18, 2026
Uncertainty Quantification for ABM Calibration
Sep 18, 2026
Global Sensitivity Analysis - Overview
Sep 18, 2026
Local vs Global Sensitivity Analysis
Sep 18, 2026
Morris Elementary Effects Screening
Sep 18, 2026
Variance-Based Sensitivity and Sobol Indices
Sep 18, 2026
ABM Validation Challenges
Sep 18, 2026
Karakaya et al 2011 - Overview
Sep 18, 2026
Logit Purchase Decision Model
Sep 18, 2026
Heterogeneity in Agent Models
Sep 18, 2026
Agent Decision Rules and Bounded Rationality
Sep 18, 2026
Homo Silicus - LLMs as Simulated Economic Agents
Sep 18, 2026
LLM Agents vs Rule-Based Agents in ABM
Sep 18, 2026
LLM-Powered Agents - Overview
Sep 18, 2026
Opinion Alignment Metrics for Language Models
Sep 18, 2026
Persona Mixture Calibration of LLM Agents
Sep 18, 2026
Silicon Samples and Algorithmic Fidelity
Sep 18, 2026
Expected Information Gain
Sep 18, 2026
Lindley's Information Measure
Sep 18, 2026
Nested Estimation and Nested Monte Carlo
Sep 18, 2026
Sequential and Adaptive BED
Sep 18, 2026
Adaptive Contrastive Estimation (ACE)
Sep 18, 2026
High-Dimensional Design Applications
Sep 18, 2026
Likelihood-Free ACE and Gradient Estimation
Sep 18, 2026
Prior Contrastive Estimation (PCE)
Sep 18, 2026
From Designs to Policies (Deep Adaptive Design)
Sep 18, 2026
Open Challenges and Future Directions
Sep 18, 2026
Approximate Thompson Sampling and Practical Extensions
Sep 18, 2026
Bernoulli Bandit and Thompson Sampling Algorithm
Sep 18, 2026
Contextual and Linear Bandits
Sep 18, 2026
Multi-Armed Bandits and Thompson Sampling - Overview
Sep 18, 2026
Regret Bounds for Thompson Sampling
Sep 18, 2026
UCB and Greedy Algorithms for Bandits
Sep 18, 2026
Convergence Rates and Estimator Selection
Sep 18, 2026
Implicit Likelihood Estimator
Sep 18, 2026
Variational Marginal Estimator
Sep 18, 2026
Variational NMC Estimator
Sep 18, 2026
Variational Posterior Estimator (Barber-Agakov)
Sep 18, 2026
Bayesian Inverse Probability Weighting
Sep 18, 2026
Bayesian Outcome Models
Sep 18, 2026
General Structure of Bayesian Causal Inference
Sep 18, 2026
Propensity Score in Bayesian Causal Inference
Sep 18, 2026
A-learning and Robustness
Sep 18, 2026
Dynamic Treatment Regimes Framework
Sep 18, 2026
Optimal Regime via Dynamic Programming
Sep 18, 2026
Q-learning
Sep 18, 2026
Causal Estimands
Sep 18, 2026
Frequentist Causal Estimation
Sep 18, 2026
Potential Outcomes Framework
Sep 18, 2026
Instrumental Variables and Principal Stratification
Sep 18, 2026
Sensitivity Analysis in Observational Studies
Sep 18, 2026
Time-Varying Treatments and G-computation
Sep 18, 2026
Bayesian Structural Time-Series Model
Sep 18, 2026
CausalImpact Empirical Application
Sep 18, 2026
Counterfactual Impact Estimation
Sep 18, 2026
Local Linear Trend and Seasonality
Sep 18, 2026
MCMC Inference for CausalImpact
Sep 18, 2026
Spike-and-Slab Prior for Covariate Selection
Sep 18, 2026
Linear-Gaussian State-Space Models
Sep 18, 2026
Marginal Likelihood via the Kalman Filter
Sep 18, 2026
State-Space Models and the Kalman Filter - Overview
Sep 18, 2026
The Kalman Filter
Sep 18, 2026
The RTS Smoother
Sep 18, 2026
Metalearner Simulation Results
Sep 18, 2026
Metalearners for CATE
Sep 18, 2026
S-Learner
Sep 18, 2026
T-Learner and Minimax Rate
Sep 18, 2026
X-Learner
Sep 18, 2026
Amortized vs Sequential Inference
Sep 18, 2026
Benchmarking and Diagnosing SBI (SBC, Coverage, C2ST)
Sep 18, 2026
Neural Likelihood Estimation and Sequential Neural Likelihood
Sep 18, 2026
Neural Posterior Estimation (NPE)
Sep 18, 2026
Neural Ratio Estimation
Sep 18, 2026
Neural SBI for Agent-Based and Economic Models
Sep 18, 2026
Normalizing Flows as Conditional Density Estimators
Sep 18, 2026
Diagnosing Variational Inference (PSIS k-hat and VSBC)
Sep 18, 2026
Mean-Field Family and Coordinate Ascent VI (CAVI)
Sep 18, 2026
Normalizing Flows for Variational Inference
Sep 18, 2026
Reparameterization Trick and Variational Autoencoders
Sep 18, 2026
The ELBO and KL Divergence Minimization
Sep 18, 2026
Variational Inference - Overview
Sep 18, 2026
Asymptotics and Frequentist Connections
Sep 18, 2026
Empirical Bayes - Overview
Sep 18, 2026
Empirical Bayes Interpretation of Shrinkage
Sep 18, 2026
James-Stein Estimator
Sep 18, 2026
Robbins Formula and Poisson Empirical Bayes
Sep 18, 2026
Stein's Paradox and Risk Dominance
Sep 18, 2026
Hierarchical Models
Sep 18, 2026
Partial Pooling as Multiple Comparisons Correction
Sep 18, 2026
Data Collection Models
Sep 18, 2026
Decision Analysis
Sep 18, 2026
Overfitting and Information Criteria
Sep 18, 2026
Global-Local Shrinkage Priors
Sep 18, 2026
Horseshoe and Regularized Horseshoe Priors
Sep 18, 2026
Spurious Association and Confounds
Sep 18, 2026
Chaos and Phase-Insensitive Statistics
Sep 18, 2026
Synthetic Likelihood - Overview
Sep 18, 2026
Constructing Priors for Effect Sizes
Sep 18, 2026
From Inference to Decision
Sep 18, 2026
Modeled and Unmodeled Data
Sep 18, 2026
Poststratification
Sep 18, 2026
Prior Distributions
Sep 18, 2026
Prior Predictive Checking
Sep 18, 2026
Relating a Model to Subject-Matter Assumptions
Sep 18, 2026
Simulation to Express Uncertainty
Sep 18, 2026
Tail Behavior and Prior-Likelihood Conflict
Sep 18, 2026
Building Up to a Hierarchical Model - Coronavirus Testing
Sep 18, 2026
Model Building - Time-Series Decomposition for Birthdays
Sep 18, 2026
Modeling Ideas to Address Computing Problems
Sep 18, 2026
Simulation-Based and Amortized Inference
Sep 18, 2026
Variational Inference and Pathfinder
Sep 18, 2026
Data-Averaged Posterior Self-Consistency
Sep 18, 2026
Comparing Models Visually
Sep 18, 2026
Cross Validation Checking
Sep 18, 2026
Influence of Individual Data Points
Sep 18, 2026
Influence of Likelihood and Prior
Sep 18, 2026
Model Selection and Overfitting
Sep 18, 2026
Posterior Predictive Checking
Sep 18, 2026
Topology of Models
Sep 18, 2026
Varieties of Bayesian Theory
Sep 18, 2026
Interpreting SBC Histograms
Sep 18, 2026
Rank Statistics and Uniformity
Sep 18, 2026
Simulation-Based Calibration - Overview
Sep 18, 2026
Cross-Fitting and Sample Splitting
Sep 18, 2026
DML Estimators for ATE and the Interactive Model
Sep 18, 2026
Generalized Random Forests - Local Moment Equations
Sep 18, 2026
Honest Trees and Causal Forests
Sep 18, 2026
Neyman Orthogonality
Sep 18, 2026
R-Learner and Orthogonal CATE Estimation
Sep 18, 2026
Regularization Bias and the Partially Linear Model
Sep 18, 2026
Doubly-Robust Estimands for ATT(g,t)
Sep 18, 2026
Group-Time Average Treatment Effects
Sep 18, 2026
Simultaneous Inference via Multiplier Bootstrap
Sep 18, 2026
Random Coefficients Logit Model
Sep 18, 2026
SMM Weighting Matrix and Inference
Sep 18, 2026
Standard Errors and Clustering
Sep 18, 2026
Directed Acyclic Graphs
Sep 18, 2026
Fisher Randomization Test and the Sharp Null
Sep 18, 2026
Permutation Tests and Exact Inference
Sep 18, 2026
Randomization Inference - Overview
Sep 18, 2026
Sharp vs Weak Null Hypotheses
Sep 18, 2026
Studentized Randomization Tests
Sep 18, 2026
The Selection Problem
Sep 18, 2026
DAGs and Causal Identification
Sep 18, 2026
Differences-in-Differences
Sep 18, 2026
Generalized Synthetic Control Method
Sep 18, 2026
Instrumental Variables
Sep 18, 2026
Local Average Treatment Effects
Sep 18, 2026
Common Support and Overlap
Sep 18, 2026
Propensity Score Matching - Balancing Theorem and Failure Modes
Sep 18, 2026
Propensity Score Matching - Overview
Sep 18, 2026
Propensity Score and the Balancing Property
Sep 18, 2026
Synthetic Control Bias Theory
Sep 18, 2026
Synthetic Control Extensions
Sep 18, 2026
Synthetic Control Inference and Diagnostics
Sep 18, 2026
Synthetic Control Requirements
Sep 18, 2026
Synthetic Control
Sep 18, 2026
Honest DiD - Sensitivity to Parallel Trends Violations
Sep 18, 2026
Pre-Trend Testing and Its Pitfalls
Sep 18, 2026
SDID Estimator - Unit and Time Weights
Sep 18, 2026
SDID Inference - Bootstrap, Jackknife and Placebo
Sep 18, 2026
SDID for Geo Experiments and Marketing Panels
Sep 18, 2026
SDID vs DiD vs Synthetic Control
Sep 18, 2026
Gaussian Local Prior Approximation
Sep 18, 2026
Plausible GMM - Institutions and GDP Application
Sep 18, 2026
Plausible GMM - Overview
Sep 18, 2026
Plausible Moment Restriction Model
Sep 18, 2026
Conditional Independence Assumption
Sep 18, 2026
Omitted Variables Bias
Sep 18, 2026
Regression and the Conditional Expectation Function
Sep 18, 2026
Conformal Inference for Counterfactuals and ITEs
Sep 18, 2026
Conformal Prediction - Overview
Sep 18, 2026
Conformal Prediction Under Covariate Shift
Sep 18, 2026
Conformalized Quantile Regression
Sep 18, 2026
Marginal vs Conditional Coverage
Sep 18, 2026
Split Conformal Prediction and the Coverage Guarantee
Sep 18, 2026
DeepAR and Global Autoregressive Neural Forecasters
Sep 18, 2026
Forecast Evaluation and Backtesting
Sep 18, 2026
Local vs Global Forecasting Models
Sep 18, 2026
Probabilistic Forecasting - Overview
Sep 18, 2026
Proper Scoring Rules (CRPS, Log Score, Pinball Loss)
Sep 18, 2026
Time-Series Foundation Models (Chronos)
Sep 18, 2026
Autoregressive Language Modeling and Pretraining
Sep 18, 2026
Compute-Optimal Training (Chinchilla)
Sep 18, 2026
In-Context Learning and Few-Shot Prompting
Sep 18, 2026
Neural Scaling Laws
Sep 18, 2026
Transformers and LLM Foundations - Overview
Sep 18, 2026
BG-NBD Model
Sep 18, 2026
Customer Lifetime Value - Overview
Sep 18, 2026
Gamma-Gamma Model of Monetary Value
Sep 18, 2026
Pareto-NBD Model
Sep 18, 2026
RFM Sufficient Statistics and Iso-Value Curves
Sep 18, 2026
Shifted-Beta-Geometric Model for Contractual Retention
Sep 18, 2026
Geo-Experiment Design and Power Analysis
Sep 18, 2026
Geo-Experiment Methodology - Overview
Sep 18, 2026
TBR Design Sensitivity and the Stationarity Assumption
Sep 18, 2026
Time-Based Regression Estimator for Geo Experiments
Sep 18, 2026
Conversion Lift Studies on Ad Platforms
Sep 18, 2026
Experimental Benchmarks for Observational Ad Measurement
Sep 18, 2026
From ITT to Treatment-on-the-Treated in Ad Experiments
Sep 18, 2026
Identity Fragmentation and the Privacy-Era Limits of User-Level Tests
Sep 18, 2026
Intent-to-Treat, PSA and Ghost Ad Designs
Sep 18, 2026
Predicted Ghost Ads and Ghost Bids Mechanics
Sep 18, 2026
User-Level Ad Experiments - Overview
Sep 18, 2026
User-Level vs Geo-Level Experiments - When to Use Which
Sep 18, 2026
Further Topics in ODE Solvers
Sep 18, 2026
ODE Filters and Smoothers
Sep 18, 2026
Solving ODEs as Inference
Sep 18, 2026
Theory of ODE Filters and Smoothers
Sep 18, 2026
Bayesian Filtering and Smoothing
Sep 18, 2026
Gauss-Markov Processes and SDEs
Sep 18, 2026
Gaussian Process Regression
Sep 18, 2026
Hierarchical Inference in Gaussian Models
Sep 18, 2026
Uncertainty Calibration for Linear Solvers
Sep 18, 2026
Acquisition Functions
Sep 18, 2026
Bayesian Optimisation
Sep 18, 2026
Value Loss and Entropy Search
Sep 18, 2026
Activity Bias in Advertising
Sep 18, 2026
Bandit Models with Delayed and Censored Feedback
Sep 18, 2026
Delayed Feedback Model for Conversion Prediction
Sep 18, 2026
Delayed and Censored Feedback - Overview
Sep 18, 2026
EM and Gradient Optimization for the Delayed Feedback Model
Sep 18, 2026
Always-Valid p-values and the mSPRT
Sep 18, 2026
Confidence Sequences
Sep 18, 2026
Interference and Marketplace Experiments
Sep 18, 2026
Switchback Experiment Design and Analysis
Sep 18, 2026
Power Analysis and Sample Size
Sep 18, 2026
Type S and Type M Errors
Sep 18, 2026
Forking Paths and Bayesian Approaches
Sep 18, 2026
Garden of Forking Paths
Sep 18, 2026
Logic of Regression Adjustment
Sep 18, 2026
Multiple Comparisons - Bayesian Perspective
Sep 18, 2026
Nuisance Parameter Bias Simulation
Sep 18, 2026
Observational vs Experimental Methods in Advertising
Sep 18, 2026
Limits and Objections to Pre-registration
Sep 18, 2026
Pre-analysis Plans and the Open Science Ecosystem
Sep 18, 2026
Prediction vs Postdiction
Sep 18, 2026
Researcher Degrees of Freedom
Sep 18, 2026
Table 2 Fallacy
Sep 18, 2026
Within-Between Persons Causal Inference
Sep 18, 2026
Ben Said et al 2002 - Overview
Sep 18, 2026
ABM Methodology and Principles
Sep 18, 2026
Emergent Phenomena in ABM
Sep 18, 2026
Opinion Leaders and Social Influence
Sep 18, 2026
Word of Mouth Mechanisms
Sep 18, 2026
Code Prompts for Causal Structure: Encoding Causal Graphs with Conditional Statements
Sep 18, 2026
Fine-tuning on Conditional Statements: Improving LLM Causal Reasoning via Code Training
Sep 18, 2026
LLM Causal Reasoning Tasks: Abductive NLG and Counterfactual Reasoning
Sep 18, 2026
Li et al. 2022 - Bayesian Causal Inference: A Critical Review
Sep 18, 2026
Approximation Methods
Sep 18, 2026
Introduction to Bayesian Computation
Sep 18, 2026
MCMC Basics
Sep 18, 2026
Automatic Differentiation Variational Inference (ADVI)
Sep 18, 2026
Stochastic and Black-Box Variational Inference
Sep 18, 2026
Probability and Bayesian Inference
Sep 18, 2026
Single-Parameter Models
Sep 18, 2026
Model Comparison
Sep 18, 2026
Generalized Linear Models
Sep 18, 2026
Bayesian Workflow Book - Overview
Sep 18, 2026
Designing Simulated-Data Experiments
Sep 18, 2026
Models for Regression Coefficients and Variable Selection - Student Grades
Sep 18, 2026
Approximations Based on Joint and Conditional Posterior Modes
Sep 18, 2026
Model Expansion - Predictive Consistency and Coherence
Sep 18, 2026
Model Selection Using Predictive Performance
Sep 18, 2026
Stacking and Predictive Model Averaging
Sep 18, 2026
From Inference to Data Analysis to Workflow
Sep 18, 2026
There Is No Safe Haven
Sep 18, 2026
SBC Case Studies
Sep 18, 2026
The SBC Algorithm
Sep 18, 2026
Adjunctions via Initial Objects
Sep 18, 2026
Pullbacks
Sep 18, 2026
Markov and Faithfulness Assumptions
Sep 18, 2026
Aggregating Group-Time Effects
Sep 18, 2026
Identifying Assumptions for Staggered DiD
Sep 18, 2026
Quantile Regression
Sep 18, 2026
Covariate Balance and Matching Diagnostics
Sep 18, 2026
Matching Algorithms and Caliper
Sep 18, 2026
Matching Methods and Distance Measures
Sep 18, 2026
Event Study Designs and Dynamic Treatment Effects
Sep 18, 2026
Synthetic Difference-in-Differences - Overview
Sep 18, 2026
Conformity Scores and Adaptive Prediction Sets
Sep 18, 2026
Hierarchical Forecast Reconciliation (MinT)
Sep 18, 2026
Scaled Dot-Product and Multi-Head Attention
Sep 18, 2026
Transformer Architecture and Positional Encoding
Sep 18, 2026
Index: Machine Learning and AI
- type/index
- source/ingested
Sep 18, 2026
Quantum Entanglement
Sep 18, 2026
Quantum Mechanics - Key Phenomena
Sep 18, 2026
Quantum Mechanics - Mathematical Formalism
Sep 18, 2026
Quantum Mechanics - Overview
Sep 18, 2026
Schrödinger Equation and Time Evolution
Sep 18, 2026
Wave Function and Hilbert Space
Sep 18, 2026
Canonical Quantization of Fields
Sep 18, 2026
Gauge Theory - Overview
Sep 18, 2026
QED and Renormalization
Sep 18, 2026
Quantum Field Theory - Overview
Sep 18, 2026
Renormalization
Sep 18, 2026
Standard Model and Gauge Groups
Sep 18, 2026
Yang–Mills Theory and Gauge Fields
Sep 18, 2026
Bayesian Quadrature
Sep 18, 2026
Sample Ratio Mismatch and Trustworthiness Checks
Sep 18, 2026
Fixed-Effects Model
Sep 18, 2026
Adjoint Functor Theorems
Sep 18, 2026
Cartesian Closed Categories
Sep 18, 2026
SMM Estimation of Factor Copulas
Aug 18, 2026
How to Get the Most Out of Bayesian Data Analysis
Aug 18, 2026
Statistical and Computational Workflow for Bayesians and Non-Bayesians
Aug 18, 2026
A Data Model Is Not Just a Likelihood
Aug 18, 2026
Causal Inference as Generalization
Aug 18, 2026
Choosing an Initial Model
Aug 18, 2026
Expressing a Bayesian Model with Probability Distributions
Aug 18, 2026
Generative and Partially Generative Models
Aug 18, 2026
Joint Priors and Covariance Matrices
Aug 18, 2026
Point Estimates and Uncertainties
Aug 18, 2026
Simulating an Underlying Process, Data Collection, and Inference
Aug 18, 2026
Specifying the Data Model and the Prior
Aug 18, 2026
Challenge of Multimodality - Differential Equation for Planetary Motion
Aug 18, 2026
Coding a Series of Models - Movie Ratings
Aug 18, 2026
Debugging a Model - World Cup Football
Aug 18, 2026
Incremental Development and Testing - Black Cat Adoptions
Aug 18, 2026
LOO Model Checking and Comparison - Roaches
Aug 18, 2026
Model Building and Expansion - Golf Putting
Aug 18, 2026
Model Building with Latent Variables - Animal Movement
Aug 18, 2026
Posterior Predictive Checking - Stochastic Learning in Dogs
Aug 18, 2026
Predictive Model Checking and Comparison - Clinical Trial
Aug 18, 2026
Prior Specification for Regression Models - Sleep Study
Aug 18, 2026
Sampling Problems with Latent Variables - No Vehicles in the Park
Aug 18, 2026
Simulation-Based Calibration Checking in Model Development Workflow
Aug 18, 2026
Using a Fitted Model for Decision Analysis - Classification Competition
Aug 18, 2026
Approximate Algorithms and Approximate Models
Aug 18, 2026
Chains, Iterations, and Effective Sample Size
Aug 18, 2026
Divide-and-Conquer Algorithms
Aug 18, 2026
Effective Sample Size and Monte Carlo Standard Error
Aug 18, 2026
Failure Modes and Steps Forward
Aug 18, 2026
Fit Fast, Fail Fast
Aug 18, 2026
Fitting Simpler Models for Computational Purposes
Aug 18, 2026
How Many Digits to Report
Aug 18, 2026
Initial Values, Adaptation, and Warmup
Aug 18, 2026
Statistical Modeling as Software Development
Aug 18, 2026
The Typical Set and the Log Posterior Density
Aug 18, 2026
What to Do About Convergence Problems
Aug 18, 2026
Big Data Need Big Models
Aug 18, 2026
Simulated-Data Experimentation as Virtual Replication
Aug 18, 2026
Software Assisted Workflow
Aug 18, 2026
Statistical and Scientific Inference
Aug 18, 2026
The Replication Crisis and Multiple Levels of Variation
Aug 18, 2026
Visualizing High-Dimensional Inference
Aug 18, 2026
Bioassay - A First Probabilistic Program
Aug 18, 2026
Computational Tools and Probabilistic Programming
Aug 18, 2026
Four Modeling Scenarios
Aug 18, 2026
Multiple-Choice Exam - A Full Workflow Walkthrough
Aug 18, 2026
Why Bayes - Benefits, Costs, and Borders
Aug 18, 2026
SBC in the Workflow
Jul 01, 2026
Bayesian Data Analysis 3rd Edition - Overview
Jul 01, 2026
Statistical Rethinking: A Bayesian Course with Examples in R and Stan
Jul 01, 2026
Mostly Harmless Econometrics: An Empiricist's Companion
Jul 01, 2026
Classical Quadrature as Inference
Jul 01, 2026
First- and Second-Order Optimisation Methods
Jul 01, 2026
Probabilistic Step-Size Selection and Line Searches
Jul 01, 2026
The Global Optimisation Problem
Jul 01, 2026
Classical ODE Solvers as Regression
Jul 01, 2026
Perturbative ODE Solvers
Jul 01, 2026
Computation as Probabilistic Inference
Jul 01, 2026
Gaussian Distributions and Algebra
Jul 01, 2026
The Numerical Agent
Jul 01, 2026
Active Bayesian Quadrature and Bayesian Monte Carlo
Jul 01, 2026
Convergence and Priors in Bayesian Quadrature
Jul 01, 2026
Kernel Quadrature and Kernel Means
Jul 01, 2026
Lessons from Integration
Jul 01, 2026
The Integration Problem
Jul 01, 2026
Classic Linear Solvers - A Review
Jul 01, 2026
Computational Constraints on Probabilistic Solvers
Jul 01, 2026
Conjugate Gradients as Probabilistic Inference
Jul 01, 2026
Gaussian Priors over Matrices and the Symmetric Kronecker Product
Jul 01, 2026
Probabilistic Linear Solvers - Algorithmic Scaffold
Jul 01, 2026
The Linear Algebra Problem and Evaluation Strategies
Jul 01, 2026
Further Topics in Global Optimisation
Jul 01, 2026
The Local Optimisation Problem
Jun 28, 2026
Population Initialization and Parameter Sensitivity
Jun 28, 2026
Sampling and Estimation for Sobol Indices
Jun 28, 2026
Summary Causal DAGs: Definition, Node Contraction, and NP-Hardness
Jun 28, 2026
BN Construction Methods Comparison
Jun 28, 2026
Choosing the Global Scale and Effective Nonzeros
Jun 28, 2026
Regularized Horseshoe (Finnish Horseshoe)
Jun 28, 2026
The Horseshoe Prior
Jun 28, 2026
Adjoint Functors
Jun 28, 2026
Units and Counits
Jun 28, 2026
Causal Discovery - Overview
Jun 28, 2026
Functional Causal Models (LiNGAM, ANM)
Jun 28, 2026
GES and Score-Based Discovery
Jun 28, 2026
PC Algorithm and Constraint-Based Discovery
Jun 28, 2026
NOTEARS - Overview
Jun 28, 2026
Factor Copulas - Overview
Jun 28, 2026
C-vines, D-vines, and Regular Vines
Jun 28, 2026
Estimation and Structure Selection for Vines
Jun 28, 2026
Pair-Copula Constructions
Jun 28, 2026
The Simplifying Assumption
Jun 28, 2026
Vine Copulas - Overview
Jun 28, 2026
BLP Demand Estimation - Overview
Jun 28, 2026
GMM Estimation and Instruments for Price Endogeneity
Jun 28, 2026
Numerical Integration and Optimization in PyBLP
Jun 28, 2026
Supply Side and Markups
Jun 28, 2026
The BLP Contraction Mapping
Jun 28, 2026
Covariate Balance Diagnostics
Jun 28, 2026
Pre-registration and Open Science - Overview
Jun 28, 2026
Pre-registration vs Registered Reports
Jun 27, 2026
Bayesian Experimental Design - Overview
Jun 27, 2026
Unified SGD BOED - Overview
Jun 27, 2026
Information-Theoretic Design Objectives
Jun 27, 2026
Modern Bayesian Experimental Design - Overview
Jun 27, 2026
Optimization and Gradient Schemes for BED
Jun 27, 2026
The Computational Revolution in EIG Estimation
Jun 27, 2026
Variational BOED - Overview
Jun 27, 2026
Nicholson's Blowfly Application
Jun 27, 2026
Q- and A-learning - Overview
Jun 27, 2026
CaGReS Algorithm: Greedy Causal DAG Summarization
Jun 27, 2026
Zeng 2025 - Overview: Causal DAG Summarization
Jun 27, 2026
Bayesian Linear Regression
Jun 27, 2026
Difference-in-Differences with Multiple Time Periods - Overview
Jun 27, 2026
Duffie-Singleton Asset-Pricing Model
Jun 27, 2026
Geometric Ergodicity and Uniform LLN
Jun 27, 2026
SME Asymptotic Distribution
Jun 27, 2026
SME Consistency
Jun 27, 2026
SME Extensions and Applications
Jun 27, 2026
Simulated Moments Estimation - Overview
Jun 27, 2026
Simulated Moments Estimator Definition
Jun 27, 2026
NOTEARS Algorithm
Jun 27, 2026
Multi-Factor and Block Dependence Structures
Jun 17, 2026
DAG Structure Learning Problem
Jun 17, 2026
NOTEARS Experiments
Jun 17, 2026
Smooth Characterization of Acyclicity
Jun 17, 2026
Factor Copula Application - S&P 100 and Systemic Risk
Jun 17, 2026
Factor Copula Construction
Jun 17, 2026
Tail Dependence in Factor Copulas
Jun 17, 2026
ABM in Marketing Strategy
Jun 17, 2026
Behavioral Attitudes in CUBES
Jun 17, 2026
s-Separation in Summary DAGs: Sound and Complete CI Identification
Jun 17, 2026
Causal Model - Cause Precondition Effect
Jun 17, 2026
Brodersen 2015 - Overview
Jun 17, 2026
Functors and Limits
Jun 17, 2026
Products and Equalizers
Jun 17, 2026
Brock-Mirman Model - SMM Estimation Exercise
Jun 17, 2026
Uncertainty Principle
Jun 17, 2026
Within-Between Persons Distinction - Overview
May 08, 2026
Categories
May 08, 2026
Functor Categories
May 08, 2026
Functors
May 08, 2026
Natural Transformations
May 08, 2026
Colimits
May 08, 2026
General Limits
May 08, 2026
Representable Functors
May 08, 2026
Yoneda Embedding and Consequences
May 08, 2026
Yoneda Lemma
May 08, 2026
Adjoints and Limits
May 08, 2026
Limits in Presheaf Categories
May 08, 2026
Limits via Representables
May 08, 2026
Universal Properties - Introduction
Apr 13, 2026
Organizational Simulation
Apr 13, 2026
CUBES Simulator Architecture
Apr 13, 2026
Garden of Forking Data
Apr 12, 2026
Consumer Utility Function Components
Apr 12, 2026
ABM vs Equation-Based Modeling
Apr 12, 2026
Product Adoption and Diffusion Models
Apr 12, 2026
Monsters and Mixtures
Apr 12, 2026
Nonparametric Models Overview
Apr 12, 2026
Multiparameter Models
Apr 12, 2026
Posterior Sampling and Summarization
Apr 12, 2026
Model Checking
Apr 12, 2026
Linear Models in Statistical Rethinking
Apr 12, 2026
SMM Python Implementation
Apr 12, 2026
Regression Discontinuity Designs
Apr 12, 2026
Canonical Causal DAGs: Node Contraction as Edge Addition
Apr 12, 2026
Statistical Rethinking: The Golem of Prague
Apr 12, 2026
Xu 2016 - Generalized Synthetic Control Method: Causal Inference with Interactive Fixed Effects Models
Apr 12, 2026
Do-Calculus in Summary Causal DAGs: Soundness, Completeness, and ATE Computation
Apr 12, 2026
Entropy-Based BN Evaluation
Apr 12, 2026
Cross-Lagged and Dynamic Panel Models
Apr 11, 2026
Estimands in Longitudinal Research
Apr 11, 2026
Research Questions in Econometrics
Apr 11, 2026
Flow Simulation Applications
Apr 11, 2026
Market and Financial Simulation
Apr 11, 2026
Operational Risk Modeling with ABM
Apr 11, 2026
Behavioral Primitives and Thresholds
Apr 11, 2026
Imitation and Conditioning Processes
Apr 11, 2026
Market Share Equilibrium and Lock-In
Apr 11, 2026
Network Topology Effects on Diffusion
Apr 11, 2026
Social Network Formation in Consumer Markets
Apr 11, 2026
Code Prompt Aspects Analysis: What Makes Code Prompts Effective for Causal Reasoning
Apr 11, 2026
Code vs Text Prompt Evaluation: LLM Causal Reasoning Benchmarks
Apr 11, 2026
Interactive Knowledge Elicitation Method
Apr 11, 2026
Liu 2025 - Overview: Eliciting and Improving Causal Reasoning in LLMs with Conditional Statements
Apr 11, 2026
NLP Causal Extraction Methods
Apr 11, 2026
Yamashita 2020 - Overview
Apr 11, 2026
Künzel 2019 - Overview
Apr 11, 2026
Missing Data Models
Apr 11, 2026
Abadie 2021 - Using Synthetic Controls: Feasibility, Data Requirements, and Methodological Aspects

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