Linked Questions
10 questions linked to/from Statistical inference under model misspecification
12
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3
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T-consistency vs. P-consistency
Francis Diebold has a blog post "Causality and T-Consistency vs. Correlation and P-Consistency" where he presents the notion of P-consistency, or presistency:
Consider a standard linear regression ...
- 69.5k
18
votes
2
answers
812
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Statistical Inference Under Misspecification
The classical treatment of statistical inference relies on the assumption that that a correctly specified statistical is used exists. That is, the distribution $\mathbb{P}^*(Y)$ that generated the ...
- 2,130
14
votes
1
answer
4k
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Is MLE estimation asymptotically normal & efficient even if the model is not true?
Premise: this may be a stupid question. I only know the statements about MLE asymptotic properties, but I never studied the proofs. If I did, maybe I woulnd't be asking these questions, or I maybe I ...
- 18.4k
9
votes
2
answers
1k
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Lasso and statistical signficance of selected variables
I'm looking at a regression model where a very large number of possible explanatory variables are being evaluated, and a small number are finally chosen via the lasso method of variable selection. The ...
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5
votes
1
answer
1k
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HAC standard error or missing ARMA terms
In the context of regressions, it seems a convention that the HAC estimator should be applied when the residual is serially correlated. But isn't the presence of residual autocorrelations an ...
- 61
11
votes
1
answer
482
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Practical usefulness of pointwise convergence without uniform convergence
Motivation
In the context of post-model-selection inference, Leeb & Pötscher (2005) write:
Although it has long been known that uniformity (at least locally) w.r.t. the parameters is an important ...
- 69.5k
8
votes
2
answers
516
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Effects of model selection and misspecification testing on inference: Probabilistic Reduction approach (Aris Spanos)
This question is about pre-test bias, inference after model selection and data snooping within the Probabilistic Reduction (PR) methodology by Aris Spanos (which is related to the Error Statistics ...
- 69.5k
5
votes
1
answer
574
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Post Model Selection Inference problems - which remedies exist?
Recently, Hannes Leeb from Yale University and Benedikt Pötscher from the University of Vienna have published a series of papers dealing with what they call Post Model Selection Inference problems.* ...
- 1,549
2
votes
1
answer
695
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When testing a hypothesis, should I keep an insignificant lag in ARMA-GARCH model?
I am trying to estimate ARMA-GARCH model for my stock returns time series.
I have estimated ARMA model for my series, and found that there exists ARCH, so added GARCH(1,1) term. However I now find ...
- 51
3
votes
1
answer
119
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Parameter Inference when Model is a bad fit to the data.
I am working with gamma-ray data from the Fermi Satellite. The data has been binned into energy dependent maps of the sky -- e.g. three dimensions (energy, latitude, longitude) and is extremely high ...
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