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in practice when the dimension of the data-generating process exceeds the sample size, this project will contribute by developing the distributional properties of generalized inverses of the high
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. The position covers four years of doctoral studies, including participation in research and doctoral courses. The last day to apply is July 12th, 2026. Project description and tasks Spatial data arise in several
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identification, and to demonstrate their effectiveness on real data. For this, we will study the model class of linear non-Hüsler–Reiss acyclic models and their generalization that includes latent variables. Our
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