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Questions tagged [skew-normal-distribution]

A family of probability distributions that includes the normal distribution as a special case, but which generalise it by allowing the distribution to be skewed.

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Finding mean and std for particles generated by crusher

I am trying to model particles generated by a mechanical crusher. We put a big chunk into crusher and we get small particles. These particles are categorised into 3 categories Size <2 mm, 2-50 mm ...
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KL divergence between normal and skewnormal distribution

I am trying to find an analytical expression for the KL divergence between a normal distribution and a skewnormal distribution. In this paper https://www.mdpi.com/1099-4300/14/9/1606 they derive the ...
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Which model for highly skewed data

The response variable in the dataset is highly skewed with a "ceiling effect". The errors of a fitted regression model, will thus also be skewed. I tried to fit a regression but as expected ...
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How can I best correct / handle a slight right skew distribution in my residuals plot using stats.models mixed effects model?

I am using statsmodels mixedlm as follows: ...
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How to test overall skewness / normality in a large data set of ordinal data in R?

I want to test overall skewness / normality in a large data set of ordinal data from survey questions and was wondering how this can be done? (I couldn’t use Shapiro wilk as I received an error saying ...
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In a skewed sample with a large n, does Central Limit Theorem dictate that a t-test can be used, even if the mean cannot be interpreted? [duplicate]

I understand that, in the case of a highly skewed population and sample, the sampling distribution of the mean can still be normally distributed if the sample size is large, according to Central Limit ...
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ANOVA: testing homogeneity of variance via D’Agostino- Pearson test?

I would be grateful for a cross-check on my understanding of the criteria for valid ANOVA analysis. The orthodoxy I've always used is the Hartley’s Fmax test, if that fails ANOVA is simply no-go. The ...
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What is the proper way to define skew distribution?

From What's the skewed-t distribution? there seems to be multiple way of defining skew distributions. However I am not sure if these methods are equivalent The original questions show methods from C. ...
Wakeme UpNow's user avatar
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Linear fit when distribution of errors is highly skewed

I have some datasets where the distribution of errors is expected to be highly skewed. I'd like to do a linear fit that takes this into account. Here is some synthetic data that shows this: ...
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Distribution closed under convolution and truncation followed by convolution

Let $D(\theta)$ denote an absolutely continuous distribution on $\mathbb{R}$. (The finite dimensional vector $\theta$ collects the parameters of the distribution.) Assume that the p.d.f. of $D(\theta)$...
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Should I take logarithm of weights in WLS regressions

I am new here. I have a question regarding the anlaytical weights used in ivreghdfe or reghdfe regressions. People usually take aweights in STATA, my question is how we deal with the weight if the ...
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How to obtain a probability distribution set that sums up to 1.0 from a PDF?

I am starting from a set of percentiles and the values at the percentile from which I fitted a skew-normal distribution. So I get a CDF and a PDF function describing the distribution. Now I'd like to ...
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Should variables be dropped according to its skewness values?

I am creating a classification model to predict the credit score of a person based on lots of factors. I got the dataset from kaggle. When I started doing the EDA part, I noticed that the skewness ...
Sounak Sarkar's user avatar
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How to find the parameters for a skewed normal distribution?

According to this website: https://datayze.com/labor-probability-calculator One can model the probability distribution function of spontaneous labour given two pieces of information. a) the due date ...
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How to generated skewed distribution with specific means and variances (in R)?

For teaching purposes I'm trying to generate some probability distributions that have varying amounts of skew but precisely controllable mean and variance. I'd like to plot these distributions and ...
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Longitudinal data model with heavy skewed data

I have 8 months of data for three groups (which belong to the same product) with three different measurements and one independent variable. I would like to perform a hierarchical multilevel model to ...
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How do I find the quartiles of a skew normal distribution parametric model of some data?

I have to program this in some environment so I won't be able to access other softwares. Let's say I've got some 50 numbers that is more or less skewed to one side. If we are to assume that it is like ...
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Mean of skew normal distribution with normal prior obtained with Gibbs sampling

I would like to obtain a new mean $\mu$ of a skew normal distribution with a normal prior of the form $N(\delta,\tau)$ on $\mu$, and a given standard deviation $\sigma$ and shape parameter $\alpha$. ...
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Generate given percentile (or data) from n, mean, median, standard deviation, p1, p25, p50, p75, p99?

I apologize if this should be asked elsewhere. I have the following information: Where N=1808 I am trying to calculate a given percentile (in this case p99.723), or ideally, if possible, generate ...
Alexander Butler's user avatar
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How to deal with skewed data?

I want to examine 2 variables of experience: A. Regular practice - hours. B. Formal practice - days. Both variables are right-skewed, with extreme outliers (Experts) and many subjects with zero ...
omer's user avatar
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Transformation of a skewed sample for estimating better the mean

Given a skewed sample whose distribution is not normal and was caused by various reasons. As a result the mean calculation is affected by the skewed distribution. Can the following steps assess the ...
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Geometry of Fisher-Pearson standardized moment

I'm studying the skewness of data distribution then the formula for measuring skewness is below: $$\tilde\mu_3 = \frac{\sum_i^N(x_i-\bar X)^3}{(N-1)(\sigma^3)}$$ I would like to understand if it is ...
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How to fit a mixed model with a skew normal distribution in python?

I am not sure if this is the best place to ask this so if not, please let me know, however I am using StatsModels to create a mixed effects model that assesses the ...
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Alternatives to Skew Normal Distribution [closed]

I'm fitting a model (using MLE) on a data set that is left-skewed. I was originally using a Gaussian log likelihood function but have been investigating whether it's possible to use Skewed Normal (SN) ...
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What distributions have one parameter that allows arbitrary skewness and is normal when the parameter is zero?

I've been working on a problem where I'm trying to resample from some data given in the form $x_{-dx}^{+Dx}$, where $x$, $x-dx$ and $x+Dx$ are the median, 16th percentile and 84th percentile. Some of ...
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Determine what range represents 95% of a skewed data set

I have a set of reference wetlands and experimentally manipulated wetlands and I am comparing many water quality variables between them. My thought was to first identify which of the manipulated ...
Dugan 's user avatar
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Skewed normal distribution

I've trained many mixed effects models and plotted the residuals vs the fitted and found this skew is appearing in many of my models. I'm unsure if this shows that normality is being violated, to me ...
Angus Campbell's user avatar
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474 views

Which test should I use to compare a normal distribution sample with skewed distribution sample?

I have two groups : Infection group (n=26) and healthy control group (n=127). The aim is to see if there is a difference in the mean of T cells absolute count* values between the two groups. Ho= the ...
Mounmoun's user avatar
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131 views

Calculating likelihood for skewed normal distribution

I would like to make a probabilistic estimate of a continuous parameter θ using Bayes' theorem. Initially, I assume that the true value of θ is equally likely to be anywhere in the interval [0,20]. ...
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What is a 'log-skew normal distribution'?

Recently, I read in a paper that they used a "log-skew normal distribution" to model returns on trades. I don't have a formal statistics background and was not aware of this distribution ...
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fitting a distribution to skewed proportional data with negative values and bounded on one side

I'm building a model to understand how different variables influence protected area performance at stopping deforestation (using counterfactual analysis). My response variable is the percentage of ...
Javier Fajardo's user avatar
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What test is appropriate for normality?

I would like to check the normality of nearly 400 individuals. I tried many test like Shapiro test, etc...but, not much expected results. So, Could you please tell me what is the appropriate test for ...
r.vijay r.vijay's user avatar
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Is skewness visible in the cumulative distribution function (cdf)?

The following two figures are the pdf's of four parametric distributions and their corresponding cdf's. The most left-ward blue line is clearly not skewed, while the most right-ward orange line is ...
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Central Limit Theorem and Skewed Distribution

I'm looking for a simple answer to this question relating the central limit theorem and Gaussian and skewed distributions, if one exists. I used the binomial function to generate calculations of the ...
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unable to remove skewness from my data

I am trying to remove skewness from my data, since my linear model requires it. e.g. all the columns in my data look like this after plotting a kde: my data contains, 0s, posituve and negative values....
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How to define a skewed distribution using mode and two inflection points? [duplicate]

I want to define a skewed distribution function and plot it in python using the mode and inflection points parameter values instead of using the mean and standard deviation. For example, I have ...
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Why does deviation from uniform distribution suggest skewed-t model may not provide adequate fits for copula model

I read a book titled "Statistics and Data Analysis for Financial Engineering with R examples". At page 203, I read the following paragraph. "Figure 8....
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Dealing with non positive definite matrix covariance (possible numeric issue)

I'm generating random number of a multivariate skew normal distribution. Here is my code: ...
Ga13's user avatar
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Finding parameters of a skew normal distribution knowing only the first and last deciles and a mean

I only know Q(0.1;…), Q(0.9;…) and the mean value, so I would like to know if there’s a way to find the parameters of skew normal distribution that fit to my data. For example, Q(0.1;…)=6670, Q(0.9;…)=...
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What distribution has exactly three parameters for mean, variance, and skewness?

Common distributions usually fix their skewness. Beta distribution has two parameters to determine all of the mean, variance, and skewness. Student-T's skewness can change by some definitions but it ...
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5 answers
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how to adjust a skewed distribution to normal?

The Totalpoints variable of the Decathlon dataset in R is a skewed distribution. How can I adjust it to normal? ...
Gump Chan's user avatar
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525 views

Generate random values to mimic skewness

I have a actual set of data where the variables are heavily skewed, both positively and negatively. I need to generate random sample data for the values going forward. The data needs to be similarly ...
Clauric's user avatar
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Generating skew-normal distribution in Matlab

My apologies if this is a trivial question, but I am having trouble with this for a while now. I need to use a skew-normal distribution in research in MATLAB and the only way I found after googling ...
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How to fit a skew normal distributon to given data?

I've got some data which I want to fit it to a skew normal distribution given by $f(z)=\frac{2}{\sigma}\phi(\frac{z-\mu}{\sigma})\Phi(\lambda\frac{z-\mu}{\sigma})$ where $\phi(z)=\frac{1}{\sqrt{2\pi}...
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Parametrization of a skew-normal distribution such that negative part is constant

I was wondering, how the parameters of the skew-normal distribution (https://en.wikipedia.org/wiki/Skew_normal_distribution) would be constrained when I require that a constant part of its support is ...
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Generating random values from a multivariate skew-normal with fixed marginals

I'm generating random values from the multivariate skew-normal, and I want that the marginal distributions from this multivariate one have fixed parameters as the following: I'm generating from ...
Ga13's user avatar
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4 votes
2 answers
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Density of sum of truncated normal and normal distribution

Suppose that $\varepsilon\sim N(0, \sigma_\varepsilon)$ and $\delta\sim N^+(0, \sigma_\delta)$. What is the density function for $X = \varepsilon - \delta$? This proof apparently appeared in a Query ...
tkmckenzie's user avatar
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1 answer
708 views

Are the skew-normal distribution and the skew-Cauchy distribution heavy-tailed?

I think the title is self-explanatory. I understand that the skewness and the tail behavior of some distribution are completely unrelated as any symmetric distribution will have a skewness of zero ...
Joy's user avatar
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Sampling from skew normal copula

For a project, I wish to draw from multivariate skew normal copulas. Initially I thought my approach was correct, but now I believe it's highly unlikely that it's correct. I've read up about the ...
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Sum of squared variables equals Chi-squared implies that the variables are standard normal?

It is known that if iid $Y_1,...,Y_n \sim N(0,1)$ than $\sum_i Y_i^2 \sim \chi^2_n$. However, if we know that (independent) $Y_1,...,Y_n$ have $\sum_i Y_i^2 \sim \chi^2_n$, can we say that $Y_1,...,...
Dave's user avatar
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