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467 |
467 |
468 .. math:: norm(μ_X + μ_Y, σ_X² + σ_Y²) |
468 .. math:: norm(μ_X + μ_Y, σ_X² + σ_Y²) |
469 |
469 |
470 https://en.wikipedia.org/wiki/Sum_of_normally_distributed_random_variables |
470 https://en.wikipedia.org/wiki/Sum_of_normally_distributed_random_variables |
471 |
471 |
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472 Sum of random number of i.i.r.v. |
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473 ================================ |
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474 |
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475 Let :math:`Y = X_1+...+X_N` is a sum of r.v. :math:`N` and all :math:`X_i` are |
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476 i.i.r.v. Thus: |
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477 |
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478 .. math:: E[Y] = E[N]·E[X] |
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479 |
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480 .. math:: var[Y] = E[N]·var(X) + var(N)·(E[N])² |
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481 |
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482 Proofs: |
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483 |
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484 .. math:: |
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485 |
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486 E[Y] = E[∑_{i=1..N}\ X_i] = E[E[∑_{i=1..n}\ X_i |N=n]] = E[∑_{i=1..n}\ E[X_i|N=n]] |
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487 |
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488 = E[∑_{i=1..n}\ E[X]] = E[N·E[X]] = E[N]·E[X] |
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489 |
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490 .. math:: |
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491 |
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492 var[Y] = E[var(Y|N)] + var(E[Y|N]) = E[var(∑_{i=1..n}\ X_i |N=n)] + var(E[∑_{i=1..n}\ X_i |N=n]) |
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493 |
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494 = E[N·var(X)] + var(N·E[X]) = E[N]·var(X) + var(N)·(E[X])² |
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495 |