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.
60 questions
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Can I use bootstrapping to estimate the uncertainty in a maximum value of a GAM?
I have data from an experiment where I look at the development of algal biomass as a function of the concentration of a nutrient. The relationship between biomass (the response variable) and the ...
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Assumptions regarding bootstrap estimates of uncertainty
I appreciate the usefulness of the bootstrap in obtaining uncertainty estimates, but one thing that's always bothered me about it is that the distribution corresponding to those estimates is the ...
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How to estimate the uncertainty in the zeros of a fitted function?
I have fitted points with a polynomial. I now have the coefficients and the covariance matrix.
For a given y (in this case y=0; that is, x is a root of the polynomial) what is the uncertainty of that ...
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Kernel density estimation incorporating uncertainties
When visualising one-dimensional data it's common to use the Kernel Density Estimation technique to account for improperly chosen bin widths.
When my one-dimensional dataset has measurement ...
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Uncertainty and sensitivity analysis
I have the following problem:
Given inputs $x$ ($n$-dimensional vector) of scalars, ordered integers and
unordered integers (i.e., labels) and one or several outputs $y$, I would
like to ...
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Derivation of uncertainty propagation?
For a function $$ y =f(x), x=\left(x_1, x_2, ..., x_N\right)$$ the law of propagation of uncertainty, see GUM sect 5$^{[1]}$ (pdf), is generally given as $$ u_y^2 = \sum_{i=1}^N \left(\frac{\partial f}...
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Calculate uncertainty of linear regression slope based on data uncertainty
How to calculate uncertainty of linear regression slope based on data uncertainty (possibly in Excel/Mathematica)?
Example:
Let's have data points (0,0), (1,2), (2,4), (3,6), (4,8), ... (8, 16), but ...
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How best to communicate uncertainty?
A massive problem in communicating the results of statistical calculations to the media and to the public is how we communicate uncertainty. Certainly most mass media seems to like a hard and fast ...
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Does it make sense to generate prediction intervals for the estimates of a logistic regression?
Say I have a binary outcome of 0 or 1 and suppose I were to use logistic regression model to estimate the probability a new sample will have an outcome of 1.
I have read answers (for example here: ...
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Is Monte Carlo uncertainty estimation equivalent to analytical error propagation?
If I have a deterministic, analytic model, $y=f(x)$, I can analytically calculate the uncertainty in $y$ from a known uncertainty in $x$, $\sigma$. Or I can do a Monte Carlo integration: sample from ...
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What is the difference between a non-zero nugget and a noise term in Kriging/GPR?
With some Gaussian Process Regression/Kriging models, it's possible to specify both a non-zero nugget, and a noise term. For example, in Scikit-learn's GPR model, there is an ...
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Risk score uncertainty quantification
I am working on various risk score estimation problems. I assume individual subjects are associated with a true risk
$$ r_i = f(x_i, \varepsilon)$$
where $x_i$ is some available information about the ...
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Fit individual-level model on aggregate-level target-data
The task is to build a regression model for individuals. I have all the independent variables for each individual, but the dependent variable only as an aggregates on group-level.
Lets say, I am ...
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Why is softmax output not a good uncertainty measure for Deep Learning models?
I've been working with Convolutional Neural Networks (CNNs) for some time now, mostly on image data for semantic segmentation/instance segmentation. I've often visualized the softmax of the network ...
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Can I convert a covariance matrix into uncertainties for variables?
I have a GPS unit that outputs a noise measurement via covariance matrix $\Sigma$:
$\Sigma = \left[\begin{matrix}
\sigma_{xx} & \sigma_{xy} & \sigma_{xz} \\ \sigma_{yx} & \sigma_{yy} &...
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