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1
Essays in Public Economics.
Essays in Public Economics.
Radler, Tyler J.Economics. | University of Michigan. | 2024
impresión
2
Taxes and Transfers, Growth and Opportunity.
Taxes and Transfers, Growth and Opportunity.
Olson, John S.Economics. | University of Michigan. | 2024
impresión
3
Statistical Methods for Multi-Omics Data in Observational Studies- [electronic resource]
Statistical Methods for Multi-Omics Data in Observational Studies- [electronic resource]
Chan, Lap Sum.Biostatistics. | University of Michigan. | 2023
impresión
4
Bayesian Models for Multi-Omic Multi-System Integration for Precision Oncology- [electronic resource]
Bayesian Models for Multi-Omic Multi-System Integration for Precision Oncology- [electronic resource]
Bhattacharyya, Rupam.Biostatistics. | University of Michigan. | 2023
impresión
5
Statistical and Computational Methods for High-Dimensional Genomics Data- [electronic resource]
Statistical and Computational Methods for High-Dimensional Genomics Data- [electronic resource]
Ma, Ying.Biostatistics. | University of Michigan. | 2023
impresión
6
Combining Adaptive Survey Design with Post-Survey Weighting Adjustment- [electronic resource]
Combining Adaptive Survey Design with Post-Survey Weighting Adjustment- [electronic resource]
Zhang, Shiyu.Survey and Data Science. | University of Michigan. | 2023
impresión
7
Methods for Summarizing and Imputing High-Frequency Digital Biomarkers in the Context of Longitudinal Data Analysis- [electronic resource]
Methods for Summarizing and Imputing High-Frequency Digital Biomarkers in the Context of Longitudinal Data Analysis- [electronic resource]
Wakim, Nicky Irene.Biostatistics. | University of Michigan. | 2023
impresión
8
Capturing Political Communication Online Using Image and Text Data: A Deep Learning Approach- [electronic resource]
Capturing Political Communication Online Using Image and Text Data: A Deep Learning Approach- [electronic resource]
Pineda, Alejandro Javier.Political Science. | University of Michigan. | 2023
impresión
9
Generalization of System Identification Objective Functions Through Stochastic Hidden Markov Models for Regularization, Smoothness, and Uncertainty Quantification- [electronic resource]
Generalization of System Identification Objective Functions Through Stochastic Hidden Markov Models for Regularization, Smoothness, and Uncertainty Quantification- [electronic resource]
Galioto, Nicholas.Aerospace Engineering. | University of Michigan. | 2023
impresión
10
Statistical Learning for Large-Scale and Complex-Structured Data.
Statistical Learning for Large-Scale and Complex-Structured Data.
Tang, Weijing.Statistics. | University of Michigan. | 2022
impresión
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