Questions tagged [uncertainty]
A broad concept concerning lack of knowledge, especially the absence or imprecision of quantitative information about a process or population of interest.
571 questions
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What are some ways to represent uncertainty on a map?
Hypothetical question, so I don't have actual data or visualization to share, but this is a problem I might face in the future.
Let's say I have a map of a region, divided by counties. I take samples ...
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Is it possible to quanify the minimum amount of information a system must acquire or infer in order to make a reliable prediction about the future?
If a predictive system operates under constraints on information storage, is it possible to formally characterize the minimum sufficient information it must retain or infer from the past in order to ...
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Calculating the average uncertainty of a set of model predictions
We use data uploaded on a citizen science platform, eBird, to estimate annual abundance trends for India’s birds. Due to the nature of birdwatching, there are some locations (sites) in the country ...
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Estimating confidence interval for parameters in a mathematical model
Say I have a nonlinear mathematical model $f$ that maps points $(u,v)$ to $(x,y,z)$:
$$
(x,y,z) = f(u,v)
$$
This model has 3 parameters: $(\phi,\theta,\psi)$.
I have $N$ correspondences:
$$
(x_i,y_i,...
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How can I estimate uncertainty in my nonlinear parameter estimation?
I am estimating the rotation $(\delta_\text{yaw}$, $\delta_\text{pitch}$, $\delta_\text{roll})$ between a camera and an Inertial Measurement Unit (IMU) both onboard a drone.
I do this by placing $N$ ...
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Determining amount of points needed to get an accurate slope with a given uncertainty
I want to determine the accuracy, uncertainty and amount of points I need for my regression analysis. I have found these (unofficial) formulas:
$$S_{xx} = \frac{N(N^2-1)}{12} (\Delta x)^2$$
$$\sigma_m ...
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Is cross-validation necessary for hyperparameter selection when bootstrapping various models?
I am attempting to evaluate the variance in performance for different logistic regression models using a bootstrapping scheme. My current idea is to use cross-validation within each replicate to ...
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How to compare WT vs mutant predictions with MC Dropout ensemble (M=5, T=100) in a binary classifier?
I’m using an ensemble of M = 5 deep neural networks, each evaluated with T = 100 Monte Carlo dropout samples at test time to estimate predictive uncertainty.
The model performs binary classification (...
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Why does the population size not affect parameter uncertainty?
I am looking to quantify the uncertainty about a parameter of a finite population, from a Bayesian perspective.
Example.
For example, we consider the proportion of people with a gym membership in ...
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How to interpret posterior uncertainty (e.g., credible intervals) under model misspecification?
In Bayesian inference, when the model is well-specified, and the prior is reasonable with respect to the true parameter of the model, the posterior is guaranteed to be well-calibrated under fairly ...
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Best way to present vectors/tensors with correlated elements
When analysing a molecular dynamics simulation, I get a tensor (3x3 matrix) at each timestep -- this is generally a function of the individual atomic positions in the simulation, $\mathbf{T}_i=f(\...
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Uncertainty ellipse on (x, y) location using azimuthal measurements from network of points [closed]
I am working on a problem relating to the 'distinguishability' of a source, that is, given a network of points in space where measurements of the azimuth to the source can be made, I would like make a ...
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Re-calculate GAM p-values to reflect uncertainty in the smoothing parameter
This is a re-post of my question here (has votes to migrate, but also required data). I can delete this version and follow instructions to migrate my OP properly, if that's preferred.
This is more of ...
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Defining epistemic and aleatoric uncertainty in GPR
Gaussian Process Regression (GPR) enables uncertainty quantification by modeling the posterior distribution of functions. Given observed data, the latent function is the mean of the posterior ...
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Variance of AUROC estimate when AUROC == 1
I am computing AUROC estimates and corresponding variances / confidence intervals. Some of my samples happen to have AUROC == 1, i.e., all positive examples are ranked above all negative examples. ...
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