PhD student.

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revised Find the degrees of freedom of a F distribution given its 97.5th percentile
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revised Find the degrees of freedom of a F distribution given its 97.5th percentile
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comment Find the degrees of freedom of a F distribution given its 97.5th percentile
Sorry, you're obviously right. I meant an F distribution, with the same dof at the numerator and denominator. Will fix my question immediately.
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asked Find the degrees of freedom of a F distribution given its 97.5th percentile
Aug
29
awarded Notable Question
Jul
2
awarded Curious
May
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awarded Tumbleweed
May
20
asked Poisson regression on partially missing covariates
May
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comment Can I trust a model if I do not check the prediction error?
Related to Glen_b's comment: darden.virginia.edu/web/uploadedFiles/Darden/Faculty_Research/…
Apr
25
comment Normalization of dummy variables
You might find this paper by A. Gelman interesting stat.columbia.edu/~gelman/research/published/standardizing7.pdf
Mar
12
comment Simulate predicted probabilities after a logistic regression
See here: stata.com/support/faqs/statistics/…
Feb
16
awarded Yearling
Feb
16
awarded Yearling
Jan
2
awarded Nice Answer
Nov
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awarded Commentator
Nov
11
comment Why do so many people apply to so few PhD programs?
PhD students are not chosen randomly from those who apply!
Oct
10
comment SNP genotype coding in regression
It should be the other way around. If you're assuming a gene-dosage effect you have only one parameter and it's a one degree of freedom test. If you dpn't assume the gene-dosage effect, you have 2 parameters and if you want to test them jointly it's a 2 dof test.
Oct
5
comment Concerns about the size of odds-ratio estimates in binary logistic regression model
$\exp(0)=1$ and not $0$ (in the last row, [L1 Reading=0])
Oct
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awarded Yearling
Sep
30
comment Difference between Maximum a posteriori and penalized likelihood
I don't know if this can be of any help, but - for example - quadratic loglikelihood penalization (squared $L_2$ norm) corresponds to having independent normal priors on the model parameters. I don't know the deatils of the paper you're referring to, but it's definitely not impossible to "exploit" PL for that purpose - Or maybe I've misunderstood your question?
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