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Random WALK, BROWNIAN MOTION and SDEs
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SDE Modeling Example 1: Population dynamics (single species) with demographic variability ππ₯=(ππ₯βππ₯)ππ‘+ ππ₯+ππ₯ π π΅ π‘ π₯: population size π: birth rate π: death rate
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SDE Modeling Example 2: Lotka-Volterra Predator-Prey π π₯ 1 = π 1 β π 1 π₯ 2 π₯ 1 ππ‘+ π 1 + π 1 π₯ 2 π₯ 1 π π΅ 1π‘ π π₯ 2 =( π 2 π₯ 1 β π 2 ) π₯ 2 ππ‘+ ( π 2 π₯ 1 + π 2 ) π₯ 2 π π΅ 2π‘ π₯ 1 : prey population size; π₯ 2 : predator population size π 1 : prey birth rate; π 2 : predator birth rate due to prey utilization π 1 : prey death rate due to predation; π 1 : predator death rate
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SDE Modeling Example 3: Population dynamics (single species) with parameter (environmental) variability ππ₯= ππ₯βππ₯ ππ‘ ππ= π½ 1 ( π 1 βπ)ππ‘+ π 1 π π΅ 1π‘ ππ= π½ 2 ( π 2 βπ)ππ‘+ π 2 π π΅ 2π‘ π½ 1 ( π 1 βπ) represents the probability associated with drift toward the mean value π 1 (average per capita birth rate in the environment). π½ 2 ( π 2 βπ) represents the probability associated with drift toward the mean value π 2 (average per capita death rate in the environment). The dynamics of the parameters follow the Ornstein-Uhlenbeck process.
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SDE Modeling Example 4: Vasicek model for interest rates ππ=π½(πβπ)ππ‘+ππ π΅ π‘ Example 5: Cox-Ingersoll-Ross (CIR) model for interest rates ππ=π½(πβπ)ππ‘+π π π π΅ π‘
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