Questions tagged [sensitivity-analysis]

Auxiliary methods intended to check if the outcome of an analysis strongly depends on the model assumptions, preprocessing steps, presence of outliers, etc.

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253 views

Are Latin hypercube samples uncorrelated

I understand the basics to Latin hypercube sampling, such as implemented by the algorithm LHSA mentioned in the book Design and Modeling for Computer Experiments. But I'd like to make sure: 1, n ...
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Sensitivity analysis of computationally expensive model

I have a finite element model of a geometric structure which is computationally expensive to solve. The model is parameterized with 3 parameters. Each configuration is solved for an increasing load ...
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Sensitivity analysis of machine learning techniques

As you know we can have sensitivity analysis (sensitivity of output(s) based on changing of inputs) in different kinds of regression. Can we have sensitivity analysis for machine learning techniques (...
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Sensitivity of Evolutionary algorithms to underlying random number generators

Techniques of evolutionary algorithms (EA) rely heavily on the use of random number generators (RNGs). From initial population generation, through the specific canonical operators applied to create ...
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How to perform regression with a sensitivity analysis in R

Without using non-base packages like plm, how can I perform a fixed effects regression in R with a sensitivity analysis for one or several other variables? Some ...
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Assessing predictor contribution to model output

Many of machine learning methods are considered as "black boxes". Examples of such methods are SVM, Neural Networks, Random forests etc. One may apply sensitivity analysis techniques (as described for ...
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How to model data

I am attempting to model a specific variable's sensitivity to a feature set. In concrete terms, I am trying to predict the duration (PAUSE_KS) of a letter (...
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192 views

Match Right Skewed Distribution to Normal

I am running a simulation. One of my parameters is sampled from a normal distribution. I would like to perform a sensitivity analysis using a right skewed distribution. This is what I had hoped to do:...
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What are the proper ways how to add noise to a dataset? (algorithm data sensitivity analysis)

Consider: dataset defined as n datapoints x_i in m-dimensional space. And there is a label <...
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1answer
119 views

Dealing with poorly estimated/missing explanatory variable values in GLMs

Context I am using generalised linear models to analyse some ecological data looking at the relationship between the population density of moth larvae and the prevalence (%) of viral mortality in the ...
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Differences between robustness checks and sensitivity analysis

This is a bit of a terminology question, but what is the difference between a robustness check and a sensitivity analysis? For example, if performing analysis to see how sensitive (or robust) a study'...
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How good is Monte Carlo Simulation when the variable distribution is unknown?

I am reading the book "how to measure everything", there is a chapter when the author encourages the usage of Monte Carlo simulation in simulating the future events in order to get a better ...
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Aside from regression coefficients, what are commonly used approaches to measure one variable's “sensitivity” to another variable?

I am about to embark on a lengthy study for a work project. At the core of it is the need for a statistical tool to help quantify "sensitivity." I am the lead software developer on the task, but I ...
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Is there a branch of statistics that tries to explain “why” the dataset has certain statistical properties?

Suppose I have a big dataset and I compute some statistical summary of it - e.g., the correlation of one dimension with another. I think a reasonable question to ask would be "what data points ...
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Selecting uncorrelated samples from a set of bulk data that contains correlated and dependent samples

i have a set of data that is generated by expensive computational model evaluations, on a total data set of 10000 samples in 40 dimensions. This sample data set is composed of different data sets, ...
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Notation conditioned means for calculation variance based first and total order effect

Could someone maybe give an explanation and formulas in terms of sums or matrix operations for the calculation of variance based effects, and total effect indices? The information given on Wikipedia: ...
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How to evaluate a regression model's sensitivity to noise

How can I investigate the sensitivity of a regression model to noise? A basic idea is to add some (Gaussian) noise to the dependent and/or independent variables and (re)evaluate the RMSE. However, ...
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beta distributions assigned to represent uncertainty

I need to calculate the Probabilistic Sensitivity Analysis for a function. I was given this: beta distributions assigned to represent uncertainty And have this parameter with this data: ...
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Difference between Sobol indices and total Sobol indices?

Given a mathematical model $Y\widetilde Y(X_i)$, where $X_i=x_i^*$ represents a particular point estimate for input variable $X_i$. In sensitivity analysis, Sobol indices explain the importance of an ...
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How to prove it's not just a chance finding when testing several variables

If I tested several similar variables, such as socioeconomic status measures, but only a few were significant, how would I prove that it's not just a chance finding? Besides having the literature to ...
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ROC and multiROC analysis: how to calculate optimal cutpoint?

I'm trying to understand how to compute the optimal cut-point for a ROC curve (the value at which the sensitivity and specificity are maximized). I'm using the dataset ...
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How to run a sensitivity analysis with dependent variables?

I am trying to run a sensitivity analysis on an efficiency indicator: the ratio between nitrogen outputs (milk, meat, crops) and nitrogen inputs (fertilizers, cattle feed, symbiotic fixation…). I ...
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Sensitivity analysis to find out which variable has the most impact on model

I have a model which predicts contamination levels of nurses' hands after touching surfaces. It depends on 4 variables: surface contamination (V), hand contact area (A), transfer efficiency of germs ($...
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Meta-analysis and homogeneity — what did these guys do?

I appreciate any insight into this meta-analysis. This is a meta-analysis on alogliptin efficacy and safety. In the 2nd paragraph of the discussion that make this statement: Although heterogeneity ...
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1answer
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Local sensitivity around the maximum

After having inferred a statistical model for my physical system $Y=f(X_1, \dots X_n)$, I want to estimate the local sensitivity of each variable $X_i$ (one by one) around the point of maximum ...
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Sensitivity analysis for modeled time series

I have very basic knowledge of stats so my question may sound very simplistic. I have a large time series of measured data and have calibrated a model with five parameters to make predictions. I would ...
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293 views

Linearity in local sensitivity analysis

As it is know local sensitivity analysis attempt to quantify the local impact of input factors on the model, through partial derivatives: a derivative of the outputs accordingly to the inputs, when ...
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Interpreting results from Sobol sensitivity analysis in R

I'm trying to use the sobol2007 model in the R sensitivity package. I'm doing runs on a model with 26 parameters, and using 2 sets of 500 monte-carlo samples to seed the analysis, and nboot=500. This ...
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246 views

Literature on robustness of regression assumptions

In my OLS regression not all assumptions are perfectly met, but I read that due to a large sample size there is a certain robustness to assumptions (my sample is 2500 people). E.g. the DV isn't ...
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Mean and Median properties

Can somebody explain me clear the mathematical logic that would link two statements (a) and (b) together? Let us have a set of values (some distribution). Now, a) Median does not depend on every ...

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