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1500 questions
42
votes
4 answers
(Why) do overfitted models tend to have large coefficients?
I imagine that the larger a coefficient on a variable is, the more ability the model has to "swing" in that dimension, providing an increased opportunity to fit noise. Although I think I've got a reasonable sense of the relationship between the…
David Marx
- 7,127
42
votes
5 answers
How to translate the results from lm() to an equation?
We can use lm() to predict a value, but we still need the equation of the result formula in some cases. For example, add the equation to plots.
user27736
- 429
42
votes
2 answers
How to find a good fit for semi-sinusoidal model in R?
I want to assume that the sea surface temperature of the Baltic Sea is the same year after year, and then describe that with a function / linear model. The idea I had was to just input year as a decimal number (or num_months/12) and get out what the…
GaRyu
- 523
42
votes
3 answers
ANOVA on binomial data
I am analyzing an experimental data set. The data consists of a paired vector of treatment type and a binomial outcome:
Treatment Outcome
A 1
B 0
C 0
D 1
A 0
...
In the outcome column, 1…
speciousfool
- 563
42
votes
3 answers
Why is it that my colleagues and I learned opposite definitions for test and validation sets?
In my master's program I learned that when building a ML model you:
train the model on the training set
compare the performance of this against the validation set
tweak the settings and repeat steps 1-2
when you are satisfied, compare the final…
Jacob Myer
- 595
- 4
- 8
42
votes
6 answers
Inclusion of lagged dependent variable in regression
I'm very confused about if it's legitimate to include a lagged dependent variable into a regression model. Basically I think if this model focuses on the relationship between the change in Y and other independent variables, then adding a lagged…
user22109
- 451
- 1
- 4
- 3
42
votes
4 answers
Explanation of finite population correction factor?
I understand that when sampling from a finite population and our sample size is more than 5% of the population, we need to make a correction on the sample's mean and standard error using this formula:
$\hspace{10mm} FPC=\sqrt{\frac{N-n}{N-1}}$
Where…
Sara
- 1,487
42
votes
2 answers
Which statistical model is being used in the Pfizer study design for vaccine efficacy?
I know there's a similar question here:
How to calculate 95% CI of vaccine with 90% efficacy?
but it doesn't have an answer, at the moment. Also, my question is different: the other question asks how to compute VE, using functions from a R package.…
DeltaIV
- 17,954
42
votes
2 answers
Purpose of the link function in generalized linear model
What is the purpose of the link function as a component of the generalized linear model? Why do we need it?
Wikipedia states:
It can be convenient to match the domain of the link function to the range of the distribution function's mean
What's the…
Chris
- 1,339
42
votes
1 answer
Quantile regression: Which standard errors?
The summary.rq function from the quantreg vignette provides a multitude of choices for standard error estimates of quantile regression coefficients. What are the special scenarios where each of these becomes optimal/desirable?
"rank" which produces…
Jase
- 2,246
42
votes
2 answers
Which search range for determining SVM optimal C and gamma parameters?
I am using SVM for classification and I am trying to determine the optimal parameters for linear and RBF kernels. For the linear kernel I use cross-validated parameter selection to determine C and for the RBF kernel I use grid search to determine C…
Kywia
- 421
42
votes
2 answers
Pooling vs. stride for downsampling
Pooling and stride both can be used to downsample the image.
Let's say we have an image of 4x4, like below
and a filter of 2x2.
Then how do we decide whether to use (2x2 pooling) vs. (stride of 2)?
JungIn Choi
- 541
42
votes
6 answers
Why do we use loss functions to estimate a model instead of evaluation metrics like accuracy?
When building a learning algorithm we are looking to maximize a given evaluation metric (say accuracy), but the algorithm will try to optimize a different loss function during learning (say MSE/entropy).
Why are the evaluation metrics not used as…
Jesús Ros
- 548
42
votes
15 answers
The Monty Hall Problem - where does our intuition fail us?
From Wikipedia :
Suppose you're on a game show, and
you're given the choice of three
doors: Behind one door is a car;
behind the others, goats. You pick a
door, say No. 1, and the host, who
knows what's behind the doors, opens
another…
Rizwan Kassim
- 765
42
votes
3 answers
How to prove that the radial basis function is a kernel?
How to prove that the radial basis function $k(x, y) = \exp(-\frac{||x-y||^2)}{2\sigma^2})$ is a kernel? As far as I understand, in order to prove this we have to prove either of the following:
For any set of vectors $x_1, x_2, ..., x_n$ matrix…
Leo
- 2,634