Statistical Analysis Stack Exchange
Statistical Analysis Stack Exchange

Questions tagged [isotonic]

isotonic means monotone, either increasing or decreasing. Use this tag for isotonic regression (monotone regression) and other forms of order-restricted inference, like hypothesis testing with ordered alternatives.

See https://en.wikipedia.org/wiki/Isotonic_regression

There are some textbooks on order-restricted inference, like https://www.amazon.com/Restricted-Statistical-Inference-Probability-Statistics/dp/0471917877 and https://www.amazon.com/Statistical-Inference-Under-Order-Restrictions/dp/0471049700

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Is it "okay" to plot a regression line for ranked data (Spearman correlation)?

I have data for which I calculated the Spearman correlation and want to visualize it for a publication. The dependent variable is ranked, the independet variable is not. What I want to visualize is more the general trend than the actual slope, so I…
Sentry
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How to test whether $\mu_1 < \mu_2 <\mu_3$?

Suppose I have three independent groups, with mean $\mu_1,~ \mu_2,~\mu_3$ respectively. How can I test whether $\mu_1 < \mu_2 <\mu_3$ or not using $n_1,~n_2,~n_3$ samples from each group? I wish to know some general methodology, not detailed…
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Estimating latent performance potential based on a sequence of observations

Context you have 200 observations of an individual's running time for the 100 metres measured once a day for 200 days. Assume the individual was not a runner before commencement of practice Based on the observed data and the 199 other observations,…
Jeromy Anglim
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Is it right to consider the output of the neural network as its confidence in predicting the output?

Suppose I have a single output sigmoid (tanh) that is producing an output ranging [-1, +1]. Is it right to consider this output as its confidence measue of predicting the output. The output value would be between -1 and +1 but even though I have a…
London guy
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why is adaboost predicting probabilities with so little standard deviation?

I'm using several algorithms to predict a binary target. So far I tried Gradient Boosting, Random Forest, Extra Random Trees and adaboost from scikit learn. All of these algorithms appear to predict probabilities ranging from close to zero to close…
ADJ
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Binomial data analysis with all 0 responses for some treatment groups

We have a series of experiments where we measure virus transmission to plants when exposed to virus-infected insects for different time periods, so all of the experiments have similar types of independent and dependent variables. In one experiment,…
user4076
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Any good reference books/material to help me build a txn level fraud detection model?

I am looking for a book/case study etc on how to build a fraud detection model at the transaction level. Something applied rather than theoretical would be really helpful.
user3081
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Monotonic splines in Python

I am trying to find a procedure to fit data monotonically in Python. The data won’t be necessarily monotonic. I just would like to achieve a monotonic fit because of theoretical assumptions. I imagine that a way of doing that would be to run an…
Eaglez
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What are drawbacks of isotonic regression?

I have been reading about isotonic regression and it seems like a great method that will give one a monotone regression function estimator and, moreover, is free of any tuning parameters. Why are people still using alternative approaches to such…
MerylStreep
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Fitting constrained hierarchical models in JAGS

I have been doing some research on constrained models and have recently read the paper: Gunn and Dunson (2005) "A Transformation Approach for Incorporating Monotone or Unimodel Constraints", Biostatistics, 6, 434-449 In this paper they advocate…
Alan Polansky
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Why bother looking at an omnibus ANOVA when I have a priori hypotheses about group differences?

I am examining three independent groups that were measured on a continuous outcome variable. I have a priori belief that the result should be Group 1 < Group 2 < Group 3. I've been told to do an ANOVA, and then to consider doing three t-tests to…
user1205901 - Reinstate Monica
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Applying isotonic regression calibration (using PAV) to new model predictions

I'm working on classifying models for a few different projects. Several papers on the subject of calibration all suggest using isotonic regression (using PAV) to adjust the model probabilities. I like the proposed calibration step, but am unsure…
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1D weighted Isotonic Regression (PAV): a simple description of the algorithm

I have to use IsotonicRegression class from scikit-learn with non-uniform point weights: in method IsotonicRegression.fit parameter sample_weight!=None. I roughly know how the weighted PAV algorithm works, but I don't want to insert the rough…
Felix
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Should Scikit-Learn CalibratedClassifierCV isotonic mode use bucketed rates instead of the actual targets?

This is less a question about sklearn's implementation, and more theoretical. I find it weird that we'd do isotonic regression against target values in {0, 1} because that could result in very jagged results. Why not use the calibration curve to do…
Alexander Soare
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Quantifying the degree of consistency of two fitted curves

I previously asked how to estimate the latent potential of a runner who ran the 100 metres each day for 200 days. Latent skill was defined as "the latent time it would take the individual to run if they (a) applied maximal effort; and (b) had a…
Jeromy Anglim
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