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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How to deal with Bias Gradient Matrix for biased CRB(Cramér–Rao bound) calculation if the gradient matrix is m-by-n but $m \neq n$?
I am doing a model for collabrative localization and using the CRB(Cramér–Rao bound) as the localization performance measurement. I want to consider interference caused by NLOS and clutter, therefore ...
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Why is the threshold term incorporated into the weight vector in linear classifiers?
In the context of linear classifiers, such as the perceptron or logistic regression, I understand that the decision boundary is defined by a linear combination of input features and weights, plus a ...
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Expectation of reciprocal residual sum of squares
Consider an IID sample $X_1 , \cdots, X_n \in \mathbb{R}^d$, then what can we say about the expectation of the reciprocal residuals when projecting onto every other point? That is can we compute
$$
E \...
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Interpreting differences between confidence intervals with and without adjustment for clustering. Should those from adjustment be wider?
I am trying to interpret an article involving data from a cluster randomised trial, where the confidence intervals for effect sizes are said to have been adjusted 'using the standard errors of the ...
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Why do top-down approaches produce biased coherent forecasts?
The context is forecasting hierarchical time series. Section 10.4 of "Forecasting: Principles and Practice" (2nd edition) by Hyndman & Atahnasopoulos states:
One disadvantage of all top-...
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Why does increasing model complexity reduce bias over the entire data distribution?
In ML, we often talk about the bias-variance tradeoff, and how increasing model complexity both reduces bias and increases variance. I understand why increasing model complexity reduces bias at first, ...
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How to prevent a regression model from overpredicting lower values and underpredicting higher ones
I'm trying to predict rental prices for houses that are listed for sale. My training set consists of houses that are listed for rent. With the predictions, my idea is to then compute an estimate of ...
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How were the asymmetric recovery ranges in Table A5 of Appendix F from AOAC determined?
I am trying to understand how the recovery ranges in Table A5 of Appendix F from AOAC (https://www.aoac.org/wp-content/uploads/2019/08/app_f.pdf) were determined.
I did not understand how the ...
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Is there a likelihood penalization or (im)proper prior to remove estimation bias for gamma parameters?
So I am learning that maximum likelihood estimation of the parameters for a gamma distribution are biased. As far as I understand there is no guarantee in general that there exists a prior (or base ...
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Bias in treatment effect estimation (adaptive design)
could someone explain what is the source of bias of treatment effect estimation in context of adaptive designs?
The FDA guidance for industry for adaptive designs https://www.fda.gov/media/78495/...
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What to show as error-bar if the bootstrap distribution is biased?
Say I have a sample, of finite size $N$, and I compute some statistic $\theta$ from it. I want to plot this sample estimate, $\hat{\theta}$, with an error-bar.
To compute the error, I am using ...
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Question on nonlinear least squares
Consider the following equation for $Y>0$:
$$
(1) \quad \log(Y)=\log(\gamma)+\log(\alpha+\beta X)+\epsilon.
$$
Assume that $E(\epsilon| X)=c\neq 0$. What are the consequences of this assumption on ...
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Target encoding in linear regression
I have a dataset with the loss rates of each contract as dependent variable. As independent variables I have country (four values), profession (5 values) and income (continous variable). I apply ...
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Granular difference-in-differences with non-repeating unit of observation
I want to analyze changes in characteristics of job postings around an (exogenous) event. However, rather than conducting the analysis at the job poster level (e.g., a company or geographic area), my ...
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Multi-reader study design: split-plot or fully crossed?
I am a radiologist designing a study where 230 CT scans of cancer patients will be evaluated by 5 radiologists. There will be two sets of evaluations: one where radiologist is aided by an AI Computer-...