Statistical Causal Inference

Symbolic Logic

Protected: Application of causal effect estimation – Causal and adjustment effects of commercial contact

Specific applications of statistical causal inference used in digital transformation, artificial intelligence, and machine learning tasks (causal and adjusted effects of CM contact using average treatment effect ATE and average treatment effect ATT in treatment groups)
2022.04.06
Symbolic Logicグラフ理論推論技術:inference Technology数理論理学最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics関係データ学習
Symbolic Logic

Protected: Basics of Statistical Causal Effects (2)Methods Using Regression Models and Matching and Stratified Analysis

Regression modeling methods for statistical causal inference utilized in digital transformation, artificial intelligence, and machine learning tasks; causal effect estimation using matching and stratified analysis methods
2022.03.30
Symbolic Logicグラフ理論推論技術:inference Technology数理論理学最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics
Symbolic Logic

Protected: Discrepancy between correlation (regression coefficient) and causation (intervention effect)

Differences between regression coefficients and intervention effect values for digital transformation, artificial intelligence , and machine learning tasks.
2022.03.22
Symbolic Logicグラフ理論推論技術:inference Technology数理論理学最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics関係データ学習
Symbolic Logic

Protected: Introduction to Causal Inference (1) Confounding Factors and Randomized Experiments

Introduction to statistical causal inference (randomized experiments controlling for confounding factors to distinguish between causality and pseudo-correlation)
2022.03.17
Symbolic Logicグラフ理論推論技術:inference Technology数理論理学最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics
Symbolic Logic

Protected: Statistical Causal Search – Extended Approach

Extension of LiNGAM approach assumptions (linearity, acyclicity, non-Gaussianity) in statistical causal inference used in digital transformation , artificial intelligence , and machine learning tasks
2022.03.15
Symbolic Logicグラフ理論推論技術:inference Technology最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics
グラフ理論

Protected: LiNGAM with unobserved common cause (2) Approach to model unobserved common cause as a sum

LiNGAM approach to modeling unobserved common causes as sums to statistical causal inference for digital transformation, artificial intelligence , and machine learning tasks
2022.03.14
グラフ理論ベイズ推定推論技術:inference Technology最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics
グラフ理論

Protected: LiNGAM in the presence of unobserved common terms (1) Approach to explicitly incorporate unobserved common causes in the model by independent component analysis

LiNGAM approach to incorporate unobserved common causes into models with independent component analysis in statistical causal inference for digital transformation , artificial intelligence , and machine learning tasks.
2022.03.11
グラフ理論ベイズ推定推論技術:inference Technology最適化:Optimization検索技術:Search Technology機械学習:Machine Learning確率・統計:Probability and Statistics
Symbolic Logic

Protected: LiNGAM (4)Estimation of LiNGAM model (2)An approach using regression analysis and evaluation of independence

Application of LiNGAM estimation with an iterative regression distribution and independence assessment approach to statistical causal inference for use in digital transformation , artificial intelligence, and machine learning
2022.03.10
Symbolic Logicグラフ理論推論技術:inference Technology最適化:Optimization検索技術:Search Technology機械学習:Machine Learning確率・統計:Probability and Statistics
グラフ理論

Protected: Fundamentals of Statistical Causal Inference (2) – Structural Causal Models and Randomized Experiments

Structural causal models and randomized experiments as a basis for statistical causal inference for digital transformation, artificial intelligence, and machine learning tasks.
2022.02.28
グラフ理論ベイズ推定推論技術:inference Technology最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics
推論技術:inference Technology

Protected: Fundamentals of statistical causal inference (1) – Definition of causality by counterfactual model and structural equation model

Foundations of Statistical Causal Inference for Digital Transformation , Artificial Intelligence and Machine Learning Tasks: Defining Causality in Counterfactual Models and Structural Equation Models
2022.02.25
推論技術:inference Technology機械学習:Machine Learning確率・統計:Probability and Statistics
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