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Find $\text{Cov}(N_{1}(t),N_{2}(t))$

score 144 · Answer 1 · 2026-03-27 13:40:09

144

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Find $\text{Cov}(N_{1}(t),N_{2}(t))$

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score 45 · Answer 2 · 2020-04-30 15:45:28

45

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score 391 · Answer 3 · 2020-04-30 19:36:37

391

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score 21 · Answer 4 · 2026-03-28 11:53:44

21

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Are two functions of the same random variable dependent? Is there a proof for this?

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score 333 · Answer 5 · 2020-05-04 22:04:44

333

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If the Covariance between $(X,Y)$ is finite, then the second moment of $X$ is finite?

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score 242 · Answer 6 · 2020-05-05 14:16:29

242

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score 350 · Answer 7 · 2026-03-26 17:36:53

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score 21 · Answer 8 · 2026-03-28 06:41:49

21

Views

What does $cov(x_1,x_2) >> 0, cov(y_1, y_2) >> 0$ and $cov(x_1+y_1, x_2+y_2) = 0$ tell us about $x_1, x_2, y_1, y_2$?

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score 1k · Answer 9 · 2020-05-06 04:48:53

1k

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score 197 · Answer 10 · 2026-03-25 22:10:33

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score 435 · Answer 11 · 2026-02-23 06:20:33

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Covariance function of a Gaussian Process, sin and cos

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score 34 · Answer 12 · 2026-03-29 15:02:31

34

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Is there any way to estimate the covariance matrix of a nonlinear function?

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score 19 · Answer 13 · 2026-03-30 11:37:18

19

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score 186 · Answer 14 · 2026-03-30 02:07:54

186

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score 29 · Answer 15 · 2020-05-12 19:48:41

29

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Covariant derivative formula- question about change of index

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List Question

Find $\text{Cov}(N_{1}(t),N_{2}(t))$

Covariance of colored cards

Coin Flip Covariance

Are two functions of the same random variable dependent? Is there a proof for this?

If the Covariance between $(X,Y)$ is finite, then the second moment of $X$ is finite?

Multivariate normal distribution with one constant term

Squared exponential kernel with Manhatten distance does not result in positive semi-definite matrix

What does $cov(x_1,x_2) >> 0, cov(y_1, y_2) >> 0$ and $cov(x_1+y_1, x_2+y_2) = 0$ tell us about $x_1, x_2, y_1, y_2$?

Computing Covariance of Sums of i.i.d. Random Variables

How to deal with underflow issues in high-dimensional entropy calculation?

Covariance function of a Gaussian Process, sin and cos

Is there any way to estimate the covariance matrix of a nonlinear function?

Generalizations of covariance to non-linear dependencies

Application of Markov Inequality(and/or Chebyshev's Inequality) to prove multivariable case

Covariant derivative formula- question about change of index

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