# Questions tagged [transform]

If possible, use a more specific tag, such as [data-transformation], [mgf], [wavelet], or [probability-generating-fn]

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### Transforming Logistic Regression Model

I have a Logistic Regression Model in R ...
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### Why is the mean of the natural log of a uniform distribution (between 0 and 1) different from the natural log of 0.5?

For a uniformly distributed variable between 0 and 1 generated using rand(1,10000) this returns 10,000 random numbers between 0 and 1. If you take the mean, it ...
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### Can ADVI (Variational Inference) Induce Weak Multi Modality in a system with Uniform Priors, if a Gaussian Variational Family is Used

Question Set Up If I have a weakly multi modal (see below in the edit) target posterior distribution which I am aiming to approximate using ADVI (Automatic Differentiation Variational Inference) with ...
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### Transformation of Uniform Distribution to Real Number Line in ADVI

In the Automatic Differentiation Variational Inference (ADVI) paper, the authors claim to solve the VI problem in a transformed parameter space, which is over $\mathbb{R}$, in order to simplify the ...
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### How can I generate 2 sets of variables from different distributions with a correlation between them in r? [duplicate]

I am working in R and would like to generate 40 numbers from $\mathrm{N}(0,1)$ and another 40 from $\mathrm{Uniform}(0,2)$ with a negative correlation (for example: $r = -0.45$) between them. The ...
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### How to interpret hourly rate data given in one miniute intervals

I have time series data on natural gas flow, which is in units of "tonnes/hour". But the data are given in one minute intervals (each row represents a single minute of time duration). Here is a sample:...
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### What does 'km' transform in cox.zph function mean?

I'm trying to understand how cox.zph function in r programming language works and I find myself not knowing what km transform ...
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### Techniques to apply Discrete Wavelet Transform (DWT) to denoise and predict time series

I just started playing with wavelets and have been using this library (https://github.com/rafat/wavelib) to further my understanding and see if 'denoising' the series at all possible levels is ...
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### How does the inverse transform method work in discrete r.v.?

In this question How does the inverse transform method work? it's mentioned the general procedure to generate r.v. U <- runif(1e6) X <- qnorm(U) X How ...
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Let $X$ be uniform on $(-1, 2)$ and let $Y = X^2$. Find the pdf of $Y$. So far I have noted that $F_X(x) = P(X \leq x) = \int_{-1}^x \frac{1}{3} dt = \frac{1}{3}(x+1)$. Then, since $Y=X^2$, $y \in [... 1answer 152 views ### Transforming non-normal to normal distribution and back-transform I would like to transform non-normal distribution to normal distribution, and back-transform to its original state (or at least close to the original state). From this article, I've read that you can ... 0answers 56 views ### VaR/inverse cdf of transformation of normal variables I have the following exercise to solve as good preparation for an exam: NOTE:$VaR_p(X)$= Value at risk =$F^{-1}_X(p)$Consider the bivariate normal random vector$(X_1, X_2)$. The marginals are ... 1answer 125 views ### In OLS, while using log-log and linear-log transforamtions, is valid to transform some regressors only? In OLS I was wondering if it is valid to log-transform some regressors only. Specifically, continuous regressors, because it is advised not to transform binary or categorical variables. For instance, ... 1answer 50 views ### How to scale between a equal distribution and an empirical distribution I am not that good at expressing things mathematically, so I'll start with the practical problem right away: I have a set of four objects: O1, O2, O3, O4. Now I want to assign a variable that scales ... 1answer 4k views ### Interpreting adjusted R-squared of a log transformed regression model I am running a linear regression model where the dependent variable (Y) is log-transformed. I am struggling on how to interpret the adjusted R-squared of this log-transformed model that is meaningful. ... 3answers 183 views ### General approaches and techniques for developing good explanatory models for nonlinear data Various recent efforts of mine on modelling some data through logistic regression have been... not successful. While there is still more data to look at, I've been wanting to explore nonlinear ... 0answers 94 views ### A transformation from uniform random variable to Gaussian mixture I am attempting to describe a prior_transform for a multivariate Gaussian mixture in order to estimate the evidence integral of that prior convolved with another likelihood distribution. This is ... 1answer 74 views ### Likelihood of the product of a normal cdf and pdf Suppose you had a random sample of r.vs X_i , i= 1....n . What is the likelihood of 2 * pdf(x) * cdf(x) , with pdf and cdf of the standard normal distribution? 1answer 137 views ### Variance after resampling uniformly from a sample from a normal population I have recently been looking into the Bootstrap, and I was wondering, if I were to have a sample$X=\{x_1,x_2,\dots,x_N\}$that has$N$samples, all i.i.d coming from a normal distribution,$N(\mu,\...
Let's say I have some MCMC framework whereby I am estimating two parameters $$(\log\alpha,\log\beta)$$ The reason for the $\log$ functions is so that the implementation of the joint prior ...