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Comparative Codon Usage_ Human vs Worm
Comparing Human RSCU with the RSCU of Worms
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Bounded rationality, learning and expectations: A critical assessment
The rational expectations hypothesis, central to modern macroeconomics, assumes that agents make optimal use of available information and correct their expectation errors immediately and accurately. However, Vernon Smith's experimental evidence shows that individuals do not always correctly identify the source of their errors and that convergence towards efficient outcomes depends on institutional design and accumulated experience rather than perfect cognitive abilities. Complementarily, Siegwart Lindenberg's RREEMM model offers a theoretical framework that incorporates cognitive constraints, limited resources, and active motivational frameworks, explaining why agents may detect misalignments without being able to correct them or even decide not to do so due to cognitive costs or normative and social priorities. This approach combines ecological and social rationality, integrating laboratory evidence with theoretical foundations of behavioural microeconomics, and offers a more realistic perspective on expectation formation and learning in complex environments. The results suggest that effective rationality is situational, adaptive and mediated by incentives and institutions, offering a bridge between normative models of rational expectations and empirical observations of human behaviour.
Analisis Regresi Tingkat Lanjut
Analisis Regresi Tingkat Lanjut adalah ruang di mana hubungan antarvariabel mulai menunjukkan sisi liarnya—interaksi, nonlinieritas, multilevel struktur, hingga dinamika waktu. Pendekatan ini menuntut kita untuk tidak berhenti pada garis lurus, tetapi menjelajahi bentuk hubungan yang lebih kaya. Dengan model seperti regresi penalti, regresi robust, mixed models, hingga spline dan Bayesian regression, kita belajar membaca pola yang tidak tampak pada metode dasar. Tujuannya bukan sekadar meningkatkan akurasi, tetapi memahami cerita lengkap di balik data. Ketika fenomena menjadi lebih kompleks, regresi tingkat lanjut memberikan bahasa matematis yang mampu menangkap kedalaman hubungan tersebut.