User safetyduck

5 votes

2 answers

538 views

scikit learn: add lasso or ridge penalty only on subset of parameters

asked Apr 8, 2014 at 3:14

4 votes

1 answer

138 views

Is there a limiting distribution if you keep taking conjugate priors within the exponential family?

asked Aug 12, 2020 at 17:52

4 votes

1 answer

59 views

A question of semantics: is any functional of a distribution a "statistic"?

asked Jun 9, 2021 at 14:53

3 votes

0 answers

257 views

Marginal parameter estimation in copula with copula (dependence) parameter known

asked Aug 27, 2012 at 0:30

2 votes

0 answers

25 views

In Gaussian Process Regression, what kinds of information can you not put in the kernel as opposed to the mean?

asked Feb 23, 2023 at 13:07

1 vote

1 answer

389 views

What would be the interpretation of asymmetric kernels in Gaussian Process Regression?

asked Oct 1, 2021 at 12:18

1 vote

0 answers

46 views

Applying Gaussian Process Regression recursively? [duplicate]

asked Apr 7, 2022 at 15:07

1 vote

0 answers

72 views

Gaussian Process Regression prior with observations as integrals?

asked Feb 17, 2023 at 16:18

1 vote

2 answers

343 views

Why does unit root imply persistance of shocks and non-stationarity from a (stochastic) dynamic systems perspective?

asked Mar 30, 2020 at 15:13

1 vote

0 answers

19 views

Are there any good references regarding non-learnability in statistical learning theory?

asked Apr 27, 2020 at 12:35

0 votes

0 answers

128 views

Is tensorflow LKJ distribution correct?

asked Mar 20, 2020 at 12:24

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11 Questions

scikit learn: add lasso or ridge penalty only on subset of parameters

Is there a limiting distribution if you keep taking conjugate priors within the exponential family?

A question of semantics: is any functional of a distribution a "statistic"?

Marginal parameter estimation in copula with copula (dependence) parameter known

In Gaussian Process Regression, what kinds of information can you not put in the kernel as opposed to the mean?

What would be the interpretation of asymmetric kernels in Gaussian Process Regression?

Applying Gaussian Process Regression recursively? [duplicate]

Gaussian Process Regression prior with observations as integrals?

Why does unit root imply persistance of shocks and non-stationarity from a (stochastic) dynamic systems perspective?

Are there any good references regarding non-learnability in statistical learning theory?

Is tensorflow LKJ distribution correct?