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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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 ...
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Correct parameterization of a Unified Skew Normal (SUN) distribution for the maximum of correlated normal random variables

I have a vector of random variables $X=(X_1, X_2, ..., X_n)$ that follows a multivariate normal distribution with a vector of means $\mu$ and covariance matrix $\Sigma$. I am interested to find the ...
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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 ...
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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 ...
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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 ...
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1 answer
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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 ...
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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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1 answer
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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 ...
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1 answer
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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 ...
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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: ...
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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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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? ...
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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 ...
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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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1 answer
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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 ...
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4 votes
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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 ...
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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 ...
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1 answer
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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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3 votes
2 answers
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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,...,...
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Is a distribution that is normal, but highly skewed, considered Gaussian?

I have this question: What do you think the distribution of time spent per day on YouTube looks like? My answer is that it is probably normally distributed and highly left skewed. I expect there is ...
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Getting skew normal parameters from its moments

I have data on expenditure in dollars, and for set of countries i know average expenditure, sd, skewness. For example in country A mean=200\$, sd=100, skewness=1.5 and i want to estimate probability ...
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skew normal computation

I want to compute probabilities assuming data have log skew normal distribution (in R). As I couldn't find any package that directly computes log skew normal (as plnorm does log normal), I am ...
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Skewness Impact on Classification

I have a dataset with 134 attributes and my goal is to build a binary classification model. While exploring the dataset, I found that there was high skewness present in the attributes. I wanted to ...
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1 answer
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Is there a skewed probability density function that models a normal distribution with two parameters, $σ_1$ and $σ_2$?

Is there a way to model data that are skew normally distributed, but for which one builds in two seperate standard deviations? The parameter $σ_1$ should specify the 15.9% to 50% interval, whereas $...
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Does 68–95–99.7 rule apply to skewed distributions as well and are they statistically correct?

I am not much familiar with statistics, but for my current simulation, I am using it to analyze my results from Monte-Carlo simulation. I understand the 68–95–99.7 rule. However, I want to confirm (...
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4 votes
3 answers
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fitting a distribution to skewed data with negative values

I am trying to model data about altruistic behavior in a simple lab experiment. I have one value for each participant in the sample (N=479), describing how altruistic that person was. As you can see ...
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Find the error on the peak value (mode) of a skewed gaussian

I have a distribution of data that follows approximately a skewed gaussian distribution (count rate vs time). I fit the distribution with the following function in python: ...
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4 votes
1 answer
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Logistic transform of multivariate zero-mean Gaussian

Consider a multivariate logistic-normal variable $z \sim \mathcal {LN}(\mu,{\Sigma})$, where ${\Sigma}$ is and $n$-by-$n$ positive definite matrix. I mean, for $x = (x_1,\ldots,x_n)\sim \mathcal N(\mu,...
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3 answers
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Sampling from Skew Normal Distribution

I want to draw samples from a skew normal distribution as part of a matlab project of mine. I already implemented the CDF and PDF of the distribution, but sampling from it still bothers me. Sadly, the ...
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2 votes
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Is the skew normal distribution a member of the exponential family

I'm trying to proof that the skew normal distribution ist part of the exponential family, but I cannot find a solution. So is it a member of the exponential family or are my assumptions misleading? ...
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method of moments for skew normal distribution

I have a random Variable $X$ is $ SN(\lambda)$ and is pdf is given by: $f(x)=2\phi(x)\Phi(\lambda x)$. The model of the variable X is given by:$X=\frac{1}{\sqrt{1+\lambda^2}}Z_1+\frac{\lambda}{\sqrt{...
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What's the skewed-t distribution?

I have just learned GARCH model. One condition distribution of it is "sstd". One question of my coursework is to justify if the conditional distribution is skewed. I have seen another example sheet ...
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Parametric Definition of Skewed Normal Distribution with Left and Right Percentile

Is it possible to easily build a Skewed Normal Distribution with these 3 parameters? -Mean (or median) 99.7-th Percentile for data to the left of the mean (median) 99.7-th Percentile for data to the ...
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