Unanswered Questions
71,464 questions with no upvoted or accepted answers
14
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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 ...
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14
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408
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How to construct confidence limits based on small stratified samples of finite populations?
Imagine a business wishes to audit its transactions. It has a database summarizing the transactions, which constitute a sampling frame for the population. It would be time-consuming and expensive to ...
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14
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What is the KL divergence of distribution from Dirac delta?
The Kullback–Leibler (KL) divergence of two continuous distributions $P(x)$ and $Q(x)$ is defined as
$$D_{KL}(P \mid\mid Q) = \int_{X} P(x) \log{\left[\frac{P(x)}{Q(x)}\right]} dx$$
How can one ...
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14
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1
answer
952
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Bound the difference between Spearman's Correlation and Kendall's Correlation
I am trying to prove or disprove that the difference between Spearman's Correlation and Kendall's Correlation is no more than 1 (or less, the tighter the merrier).
I am assuming there are no ties.
...
CommunityBot
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14
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2k
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Negative deviance explained by GAM with betareg in R
I am fitting the following model in "mgcv" package in R using option family=betar to predict a percentage cover response variable (...
13
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0
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587
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Are there Imbalanced learning problems where re-balancing/re-weighting demonstrably improves *accuracy*?
I have been looking into the imbalanced learning problem, where a classifier is often expected to be unduly biased in favour of the majority class. However, I am having difficulties identifying ...
- 57k
13
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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
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Are these equivalent (for p-values): super-uniform, stochastically larger than / dominating the uniform, conservative?
In the literature and online, I have found three different wordings that I think refer to the same concept: stochastically larger than uniform (which I take is ...
CommunityBot
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13
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778
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Interpreting regression coefficients based on Andrew Gelman's re-scaling method
I have two predictors in a binary logistic regression model: One binary and one continuous. My primary goal is to compare the coefficients of the two predictors within the same model.
I have come ...
CommunityBot
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13
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20k
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How to find p value using estimate and standard error?
I am trying to check statement on p. 23 of Data Analysis Using Regression and Multilevel/Hierarchical Models
For example, consider two independent studies with effect estimates and standard errors ...
13
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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
13
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415
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Is autocorrelation not worth addressing with small N?
Consider a simple regression context in which there is a small set of response values, $Y$, and corresponding dates, $X$. (For simplicity, we can assume the dates are equally spaced.) We would like ...
13
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14k
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How to normalize data prior to computation of covariance matrix
In all my self-study, I have come across many different ways in which people seem to normalize their data, prior to the computation of the covariance matrix. I am confused as to what ways are 'correct'...
- 338k
12
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0
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517
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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 ...
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12
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Instrumental variables with interactions between endogenous variables
I have two endogenous variables $x_1$ and $x_2$ and am trying to estimate the following model:
$$y = \theta_0 + \theta_1 x_1 + \theta_2 x_2 + \theta_{12} x_{12}$$
where $x_{12} = x_1\times x_2$. I'm ...
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