Questions tagged [bias]
The difference between the expected value of a parameter estimator & the true value of the parameter. Do NOT use this tag to refer to the [bias-term] / [bias-node] (ie the [intercept]).
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Omitted variable bias in logistic regression vs. omitted variable bias in ordinary least squares regression
I have a question about omitted variable bias in logistic and linear regression.
Say I omit some variables from a linear regression model. Pretend that those omitted variables are uncorrelated with ...
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Bias and variance in leave-one-out vs K-fold cross validation
How do different cross-validation methods compare in terms of model variance and bias?
My question is partly motivated by this thread: Optimal number of folds in $K$-fold cross-validation: is leave-...
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Intuitive explanation of the bias-variance tradeoff?
I am looking for an intuitive explanation of the bias-variance tradeoff, both in general and specifically in the context of linear regression.
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Biased bootstrap: is it okay to center the CI around the observed statistic?
This is similar to Bootstrap: estimate is outside of confidence interval
I have some data that represents counts of genotypes in a population. I
want to estimate genetic diversity using Shannon's ...
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How to know if a learning curve from SVM model suffers from bias or variance?
I created this learning curve and I want to know if my SVM model suffers from bias or variance? How can I conclude that from this graph?
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Omitted variable bias: which predictors do I need to include, and why?
For a last couple of weeks I've been thinking about OVB (Omitted variable bias) in the context of regression and solution for that (how to avoid this problem). I am acquainted with Shalizi's lectures (...
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Power paradox: overestimated effect size in low-powered study, but the estimator is unbiased
If we have an underpowered study but manage to reject the null hypothesis, anyway, it makes sense to wonder if we have overestimated the effect size.
However, such a concern seems unwarranted if we ...
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When is a biased estimator preferable to unbiased one?
It's obvious many times why one prefers an unbiased estimator. But, are there any circumstances under which we might actually prefer a biased estimator over an unbiased one?
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Why is OLS estimator of AR(1) coefficient biased?
I am trying to understand why OLS gives a biased estimator of an AR(1) process. Consider
$$
\begin{aligned}
y_{t} &= \alpha + \beta y_{t-1} + \epsilon_{t}, \\
\epsilon_{t} &\stackrel{iid}{\...
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What is an unbiased estimate of population R-square?
I am interested in getting an unbiased estimate of $R^2$ in a multiple linear regression.
On reflection, I can think of two different values that an unbiased estimate of $R^2$ might be trying to ...
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Bias of maximum likelihood estimators for logistic regression
I would like to understand a couple of fact on maximum likelihood estimators (MLEs) for logistic regressions.
Is it true that, in general, the MLE for logistic regression is biased? I would say "yes"....
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Question about bias-variance tradeoff
I'm trying to understand the bias-variance tradeoff, the relationship between the bias of the estimator and the bias of the model, and the relationship between the variance of the estimator and the ...
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What's the difference between asymptotic unbiasedness and consistency?
Does each imply the other? If not, does one imply the other? Why/why not?
This issue came up in response to a comment on an answer I posted here.
Although google searching the relevant terms didn't ...
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When is the bootstrap estimate of bias valid?
It is often claimed that bootstrapping can provide an estimate of the bias in an estimator.
If $\hat t$ is the estimate for some statistic, and $\tilde t_i$ are the bootstrap replicas (with $i\in\{1,...
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Intuitive understanding of the difference between consistent and asymptotically unbiased [duplicate]
I am trying to to get an intuitive understanding and feel for the difference and practical difference between the term consistent and asymptotically unbiased. I know their mathematical/statistical ...
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