Design and validate original, research-style computational statistics problems that require complex reasoning and cannot be solved manually in reasonable timeframes. Use Python and standard scientific libraries (such as NumPy, SciPy, Pandas, and SymPy) to verify solutions, then clearly document both the problem statements and their fully reproducible correct solutions. The problems must reflect real-world research and applied workflows, such as estimation, inference, simulation, and optimization.
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