Unanswered Questions
6,465 questions with no upvoted or accepted answers
14
votes
0
answers
700
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Convolutional neural network for multi-variate time series?
I want to use CNN architectures for classification of multivariate time-series, where we apply one label to each sequence.
I searched the net for the available designs in the literature and i found ...
- 439
13
votes
0
answers
272
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Logistic regression for classification: are there any analytical solutions for the out-of-sample accuracy?
I run a binary logistic regression, with a binary dependent variable and a continuous independent one.
Now I want to evaluate the out-of-sample performance of the classification algorithm so obtained. ...
- 2,578
13
votes
0
answers
741
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Help me understand the Bayesian kernel density estimation (Sibisi and Skilling, 1996)
Sibisi and Skilling (1996, also mentioned in the 1997 paper) define Bayesian kernel density as
$$ f(x) = \int dx' \,\phi(x')\, K(x, x') \tag{2} $$
Here the kernel $K$ is an assigned smooth ...
- 143k
12
votes
0
answers
517
views
Official name of a common type of Bayesian simulation study
There is a kind of simulation study that is commonly used to validate an implementation of a Bayesian model:
For independent replication $i = 1, ..., n$:
Draw a set of "true" parameters ...
- 267
12
votes
0
answers
3k
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Fourier transform of a Gaussian process
I would like to discuss and ask a question regarding the Fourier transform of a Gaussian process, if it makes sense.
For that purpose, let me describe the following situation.
Let $z(s)$ be a ...
CommunityBot
- 1
12
votes
0
answers
2k
views
Computing a bootstrap confidence interval for the prediction error with the percentile and the BCa method
I have two related questions regarding the computation of a non-parametric bootstrap confidence interval for the prediction error.
Setting: I have a sample S from a data population P and a learner L, ...
CommunityBot
- 1
11
votes
0
answers
192
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Pope effect on pizza - Regression with presence absence and similarity data as dependent variables
I'm trying to figure out the right way to set up a regression when the dependent variables are presence absence data (of pizzas), and the similarity between the present pizzas. Bear with the story:
...
- 251
11
votes
1
answer
745
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Hypergeometric: how do I construct a credibility interval around K (population successes) in R?
I have a problem for which I believe I should use the hypergeometric distribution, but I can't figure out how to do it in R.
Say I have a bag of marbles with known number ($N$) of marbles, but the ...
CommunityBot
- 1
10
votes
3
answers
232
views
How to guess the size of a set?
Assume we have a set of unique words and draw a number $n$ of them using simple-random-sampling without replacement independently in each round. We have several rounds and try to guess the set size ...
CommunityBot
- 1
10
votes
0
answers
160
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Rationale behind Good–Turing frequency estimation?
Good–Turing frequency estimation is a smoothing estimator for estimating a multinomial distribution. It seems very convoluted.
From mathematical statistics point of view, what is the rationale
behind ...
- 84k
10
votes
2
answers
2k
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Random Forest: Class specific feature importance
I'm using the bigrf R-package to analyse a dataset with ca. 50.000 observations x 120 variables, classified into two groups.
After growing a forest of 1000 trees, ...
CommunityBot
- 1
9
votes
1
answer
2k
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PyMC3 implementation of Bayesian MMM: poor posterior inference
Google released a whitepaper on Media Mix Modelling (MMM) in 2017; vanilla MMM (established in the 1960s) uses multivariate regression. It's a decent mechanism to understand which of your marketing ...
CommunityBot
- 1
9
votes
1
answer
179
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Is there a ML or DL tool that can learn to detect periodically occurring patterns in a one dimensional time series?
I am trying to create a tool that labels refrigerator temperature readings. A reading is taken every 5 minutes, and its label identifies whether of not it was taken while the refrigerator was ...
- 10k
9
votes
0
answers
11k
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Singular fit with simplest random structure in lmer (lme4), is a Bayesian approach the only option?
I'm running a mixed model with the lmer function from the lme4 package in R and ran into some issues with singular fits. I get the warning message 'singular fit', ...
9
votes
0
answers
3k
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Implementing Predictive Posterior Distribution Using Stan
Background
I had an example that sought to demonstrate the posterior predictive distribution in the context of a normal measurement model. The data that was used is as follows:
...
- 2,234