# Tagged Questions

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### Gaussian Distribution Prediction

What are some common methods of making distribution predictions? I have a set of features $x_1,x_2,x_3$ which map to Gaussian distributions ($\mu,\sigma^2$). That is, the feature vector of a single ...
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### When am I allowed to make linear regression on a small sample?

I'm trying to evaluate the linear correlation between to continuous variables (% value calculated from EEG datas and the area of an anatomical region of the brain). I have a sample of 18 right now. ...
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### Integration step in Bayesian linear regression

I want to obtain the integral: \int_{{\mathbb R}^p} \frac{1}{(2\pi)^{\frac{n}{2}}\vert\Sigma\vert^{\frac{1}{2}}}\exp\left[-\frac{1}{2}({\bf y} - {\bf X}{\beta})^{\top} \Sigma^{-1}({\bf y} - {\bf ...
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### Can explanatory variables be non-Gaussian?

I am conducting a logistic regression. However, the Shapiro-Wilk test has determined that one of the X variables is non-Gaussian. Do the explanatory (X) variables need to be Gaussian? If so what are ...
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### Confusion related to predictive distribution of gaussian processes

I have this confusion related to the predictive distribution of gaussian process. I was reading this paper I didn't get how the integration gave that result. What is P(u*|x*,u). Also how come the ...
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### Heteroskedasticity and residuals normality

I have a linear regression that's quite good, I guess (it's for a university project so I don't really have to be super accurate). Point is, if I plot the residuals vs. predicted values, there is ...
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### Regression with non-normally distributed residuals

There are several posts on this site talking about the need of normality when interpreting the meaning of the p.value of a linear regression. But not much I think is said about how to deal with ...
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### What is the distribution of linear model parameters?

I am interested in testing if linear models are statistically different, so I would like to know what I can assume about the distribution of linear parameter models, like the slope for example. More ...
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### In R, find function F(x) to transform values in a vector to a normal distribution?

I have a PDF (Probability Density Function) generated from a vector of 1,000,000 empirical values. This empirical PDF is heavily skewed to the right. In this form, I can't make accurate predictions ...
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### Probit ordered model for non-normal distribution of outcomes

I have the following Y outcomes distribution with the normal density function represented by the superimposed red line: I need to develop a regression methodology to predict $Y$ given a number of ...
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### How can I prove the experiment data follows heavy-tail distribution?

I have several test results of server response delay. According to our theory analysis, the delay distribution (The probability distribution function of response delay) should have heavy-tail ...
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### Is using a questionnaire score (EuroQol's EQ-5D) with a bimodal distribution as outcome in linear regression a problem?

There is currently a debate whether the EQ-5D score that has a ceiling problem and a bimodal distribution can be used in a linear regression model or not. Background The score is very simple and ...
### Assuming $u\sim N(0,\sigma^2)$ when y is highly skewed
does it make sense to assume $u\sim N(0,\sigma^2)$ when I know from a histogram that $y$ is highly skewed. Because from the assumption $u\sim N(0,\sigma^2)$ it follows that $y\sim N(x\beta,\sigma^2)$ ...