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1500 questions
33
votes
3 answers
How do the Goodman-Kruskal gamma and the Kendall tau or Spearman rho correlations compare?
In my work, we are comparing predicted rankings versus true rankings for some sets of data. Up until recently, we've been using Kendall-Tau alone. A group working on a similar project suggested we try to use the Goodman-Kruskal Gamma instead, and…
Poik
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33
votes
3 answers
How to tell the difference between linear and non-linear regression models?
I was reading the following link on non linear regression SAS Non Linear. My understanding from reading the first section "Nonlinear Regression vs. Linear Regression" was that the equation below is actually a linear regression, is that correct? If…
mHelpMe
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33
votes
1 answer
Why are rectified linear units considered non-linear?
Why are activation functions of rectified linear units (ReLU) considered non-linear?
$$ f(x) = \max(0,x)$$
They are linear when the input is positive and from my understanding to unlock the representative power of deep networks non-linear…
Aly
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33
votes
2 answers
How to set up neural network to output ordinal data?
I have a neural network set up to predict something where the output variable is ordinal. I will describe below using three possible outputs A < B < C.
It is pretty obvious how to use a neural network to output categorical data: the output is…
Alex I
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33
votes
5 answers
Color and line thickness recommendations for line plots
Much has been written about color blind-friendly color choices for maps, polygons, and shaded regions in general (see for example http://colorbrewer2.org). I have not been able to find recommendations for line colors and varying line thickness for…
Frank Harrell
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33
votes
6 answers
Statistical classification of text
I'm a programmer without statistical background, and I'm currently looking at different classification methods for a large number of different documents that I want to classify into pre-defined categories. I've been reading about kNN, SVM and NN.…
Emil H
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33
votes
5 answers
Are decision trees almost always binary trees?
Nearly every decision tree example I've come across happens to be a binary tree. Is this pretty much universal? Do most of the standard algorithms (C4.5, CART, etc.) only support binary trees? From what I gather, CHAID is not limited to binary…
Michael McGowan
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33
votes
1 answer
Variance on the sum of predicted values from a mixed effect model on a timeseries
I have a mixed effect model (in fact a generalized additive mixed model) that gives me predictions for a timeseries. To counter the autocorrelation, I use a corCAR1 model, given the fact I have missing data. The data is supposed to give me a total…
Joris Meys
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33
votes
1 answer
Is there a way to use the covariance matrix to find coefficients for multiple regression?
For simple linear regression, the regression coefficient is calculable directly from the variance-covariance matrix $C$, by
$$
C_{d, e}\over C_{e,e}
$$
where $d$ is the dependent variable's index, and $e$ is the explanatory variable's index.
If one…
David
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33
votes
5 answers
Strategy to deal with rare events logistic regression
I would like to study rare events in a finite population. Since I am unsure about which strategy is best suited, I would appreciate tips and references related to this matter, although I am well-aware it has been largely covered. I just don't really…
Damien
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33
votes
3 answers
What is theta in a negative binomial regression fitted with R?
I've got a question concerning a negative binomial regression: Suppose that you have the following commands:
require(MASS)
attach(cars)
mod.NB<-glm.nb(dist~speed)
summary(mod.NB)
detach(cars)
(Note that cars is a dataset which is available in R,…
MarkDollar
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33
votes
7 answers
What is the name of the statistical fallacy whereby outcomes of previous coin flips influence beliefs about subsequent coin flips?
As we all know, if you flip a coin that has an equal chance of landing heads as it does tails, then if you flip the coin many times, half the time you will get heads and half the time you will get tails.
When discussing this with a friend, they said…
oggmonster
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32
votes
3 answers
How to get an "overall" p-value and effect size for a categorical factor in a mixed model (lme4)?
I would like to get a p-value and an effect size of an independent categorical variable (with several levels) -- that is "overall" and not for each level separately, as is the normal output from lme4 in R. It is just like the thing people report…
user3288202
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32
votes
5 answers
Expected prediction error - derivation
I am struggling to understand the derivation of the expected prediction error per below (ESL), especially on the derivation of 2.11 and 2.12 (conditioning, the step towards point-wise minimum). Any pointers or links much appreciated.
Below I am…
user1885116
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32
votes
1 answer
One-vs-All and One-vs-One in svm?
What is the difference between a one-vs-all and a one-vs-one SVM classifier?
Does the one-vs-all mean one classifier to classify all types / categories of the new image and one-vs-one mean each type / category of new image classify with different…
user3378327
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