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Questions tagged [surrogate]

Estimating the long-term effects of treatments is of interest in many fields. A common challenge to this is that long-term outcomes are typically unobserved in the time frame needed to make policy decisions. Instead, we can analyze effects on an intermediate outcome, termed a “statistical surrogate.” For example, in the case of studies of the effect of cancer therapies on mortality, tumor size serves as a statistical surrogate for mortality rates.

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Generating "surrogate data" to calculate error on estimators

We have a dataset in the form of a time series $Y_n$. We assume it follows an underlying parametric distribution $f(n,\beta)$, $\beta$ being the parameters. From the observed dataset, we get an ...
Barbaud Julien's user avatar
1 vote
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Imputation method for missing values that are irrelevant

I have a data set $\mathbf X$, with around 20 predictors, which is a matrix of parameters of a surrogate model. For each observation $\mathbf i$ of $\mathbf X$, the surrogate model was trained to ...
Florent H's user avatar
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Best way to fit a Gaussian Process surrogate model to an RL Reward function

Is there a way to get an estimate of good scaling parameters (namely mean and variance) for a Gaussian Process kernel serving as a surrogate model to a Reinforcement Learning reward function for ...
Prishita Ray's user avatar
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Surrogate model data requirements

I am trying to undersand how to approach the development of a surrogate model to investigate the associated uncertainty when predicting late arrival times. I.e there is an, to me, agnostic and ...
OLGJ's user avatar
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1 vote
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What is Classification Calibration Theorem?

I have heard from one of my friends "In binary classification, consider the 0-1 loss (I[y!=f(x)]). Its expectation is the accuracy of the model. Then consider a surrogate risk, like exponential ...
XYZ's user avatar
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2 votes
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How does the scale of the target value effect the Gaussian Process performance?

I am currently working with Gaussian Process to make a surrogate model for temperature prediction. A question arose when I was thinking to make result plots in Celsius instead of Kelvin. I suspect if ...
Ann's user avatar
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2 votes
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Analysis of a model response for peaks and valleys that is generated by meta-modeling

I studied biomechanics and I'm kind of new to the world of machine learning. Nevertheless it would be great to get some feedback from some experts, what is possible and what is not possible with ML. ...
user325769's user avatar
1 vote
1 answer
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Can we use Shap to interpret output changes?

Can we calculate the difference between Shapley values to interpret changes in the output? More precisely, if we get Shapley values for two different inputs, can we compare them to understand how much ...
giogix's user avatar
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What is the relation between a surrogate function and an acquisition function?

A surrogate function is a simpler function than the objective function to evaluate. An acquisition function is used to propose sampling points. In the context of Bayesian optimisation and Gaussian ...
user avatar
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1 answer
2k views

What's the difference between a "surrogate metric" and a "proxy metric"?

Is there a difference between a "surrogate metric" a "proxy metric" or a "correlated metric"? Is "surrogate" simply unnecessary jargon, or is there a meaning that makes it more specific than when ...
Harry M's user avatar
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3 votes
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Standard Error Calculation for the Statistical Surrogates Index Estimator in Athey, Chetty, Imbens, and Kang (2016)

I am trying to understand the simple surrogate index estimator from Athey, Chetty, Imbens, and Kang (2016) in Section 5.1 of v2 of their paper. The setup is that you have an experiment that alters ...
dimitriy's user avatar
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