Questions tagged [heavy-tailed]
The heavy-tailed tag has no usage guidance.
7
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2answers
281 views
Quantifying dependence of Cauchy random variables
Given two Cauchy random variables $\theta_1 \sim \mathrm{Cauchy}(x_0^{(1)}, \gamma^{(1)})$ and $\theta_2 \sim \mathrm{Cauchy}(x_0^{(2)}, \gamma^{(2)})$. That are not independent. The dependence ...
8
votes
3answers
103 views
What does it mean to say that $X_1, X_2$ have a “common” Normal distribution?
An exercise question asks
Let $X_1, X_2$ be rvs having a common Normal distribution $N(0,1)$ with $\operatorname{Corr}(X_1, X_2) = \rho$. Calculate the coefficient of upper tail-dependence for all $...
0
votes
1answer
28 views
need explanation about the exponent parameter s in zipf distribution
I need to model the popularity of some requested files from a library with Zipf distribution and I want to simulate it in MATLAB. I don't know what's the effect of parameter s on my result. for ...
3
votes
0answers
73 views
Is the truncated power law a heavy-tailed distribution?
A heavy-tailed distribution is often defined as a distribution with a tail that is not exponentially bounded.
A truncated power law (or power law with exponential cut-off) is a distribution that ...
0
votes
1answer
44 views
Transform Heavy right tailed data
I am clustering (K-MEANS) a data 1.7million observations, which displays a heavy-tailed distribution when examined by plot. What is the best transformation to correct it. does log can handle this?
1
vote
1answer
90 views
A question about qqplot
This is my qq plot :
Its concave-convex curve so it indicates light tails. But my mean excess plot :
is increases which means the tail of the distribution of my data is heavy-tailed.
I don't ...
0
votes
0answers
241 views
In a left skewed distribution, how can the range where 95% data lies?
In a simulation that I ran, I have the following graph as a result. How can I find the 95% confidence interval (i.e. the range where 95% of data lies for me).
Since I am not expert in stats, please do ...
0
votes
1answer
46 views
Decomposition of the probability of the sum
I cannot understand how is gotten the following decomposition.
Supposing that $X_1,...,X_n$ random variables i.i.d with heavy tailed distribution $S_n=\sum_{i=1}^nX_i$
In the article that I m ...
1
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0answers
46 views
Determining the distribution of data
Hi, I am a student learning financial modelling. I would like some help in determining the distribution of the data given the plots above. I am reluctant to assume normal distribution of the data due ...
0
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0answers
23 views
Selecting candidate 4- or 5- parameter flexible distributions for right-skewed, heavy-tailed data
I am engaged in fitting distributions to a number of data sets that include information on income, wealth, or consumption (and various subsets of these things such as labor or capital income) of ...
0
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0answers
23 views
Determining the number of observations within the tail of a given distribution
I am wondering how to determine the number of observations that fall within the tail of a distribution. I am reading a paper and the authors use the assumption that 50 observations need to fall into ...
0
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0answers
34 views
Left “tail” of one-tailed distributions
I think of the "tail" of a probability distribution as the behavior of its PDF $f(x)$ as $x\rightarrow +\infty$. For some PDFs with complicated expressions, it is sometimes easy to study their ...
2
votes
3answers
56 views
If the best-fitting distribution has infinite variance, should low observed variance be troubling?
Suppose you have observations which, over the observed range of outcomes, are well-fitted by some distribution like the Pareto that, for certain parameter values, has a an infinite variance. For ...
1
vote
1answer
88 views
Does the normality assumption hold? Is this an outlier?
I am trying to fit a multiple linear regression (OLS) model with IPO underpricing as dependent variable. As part of my master thesis I would like to analyze the effect of venture capital ...
2
votes
1answer
40 views
A random variable $X$ on $(0,\infty)$ which behaves like Exp for small $x$ and Pareto for large $x$
Are there any examples of distributions which behave like Exponential for small values and like Pareto for large values.
$$\ln \mathbb{P}[X>x] \sim -\lambda x, \qquad \text{ for } x \text{ small}, ...
6
votes
2answers
117 views
Regression: zeros in heavy-tailed independent variable from quantization
This question is about handling zeros in an independent variable for a regression.
In particular, the zeros are not missing data or true zeros, but occur because of quantization. As a concrete ...
1
vote
0answers
29 views
Rigorous threshold determination for heavy-tailed data?
Overview: I'm trying to design a change-point detection system for univariate, non-normal, skewed, heavy-tailed data that I believe is generated by a stable random process (i.e. stable-distributed ...
0
votes
0answers
311 views
Regression, fat tails, heteroscedasticity
I am working on a linear regression model, we want to know how $y$ is influence by $x$. Unfortunately, the data consists only of 42 points in time and a lot of negative values.
It is a time series ...
0
votes
1answer
288 views
Visual fitting of tails of density plots on log scale (R)
Density plots are useful in confirming the fit of a distribution or assessing which distribution to try in order to give the best fit. However, when looking at the tails on log scales, especially for ...
1
vote
0answers
336 views
tail dependence calculation
If I have the tail dependence value calculated using Joe (1997) in fact $R$ gives the result for any family copula. Using Caillault and Guegan method called "naive" what are the main differences? Why ...
2
votes
2answers
184 views
inferring heavy-tail distribution from finite sample of histogram data
I have some data in the form of bins and counts. Here is one complete non-truncated example:
...
2
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0answers
56 views
Parametric modelling of survival data: when there is no event in a long tail, is there information?
I have a survival analysis question. Let's take a look at the below curve:
For the red curve, there are no more events after 48 months. For the black curve, there are no more events after 60-ish ...
2
votes
1answer
55 views
On the existence of a heavy tailed c.d.f. given a condition based on the CLT
My question is about the existance of a heavy tailed distribution $F$ such that: given two i.i.d. samples $\{X_1,\ldots,X_n\}$ and $\{Y_1,\ldots,Y_n\}$, from $F$, we have
$$\sqrt{n}\frac{\hat{\mu}_X -...
0
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0answers
131 views
Relationship between the length of the whiskers and the tails of a population in boxplot
Why in the boxplots long whiskers are associated with a heavy tailed distribution and short whiskers are associated with light tailed distributions populations?
2
votes
1answer
2k views
Difference between long tail and short tail distribution?
I want to understand the difference between these distribution types.
What is the difference between a long and short-tailed distribution?
0
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1answer
73 views
how to choose a transformation for left heavy tailed data due to arbitrary upper limit imposed by experimenter?
I have two vectors that look like this:
I would like to make a significance test on the paired differences between the two vectors, as well as measure association.
The process of data generation is "...
1
vote
1answer
27 views
Are the family of stable distributions differentiable everywhere on the real line?
Are stable distributions smooth enough for each index of stability $\alpha$ between 0 and 2, and skewness parameter $\beta$ between 0 and 1?
Where there any papers that mention this?
0
votes
1answer
32 views
Is there an analytical way to find the area under the probability density function of a stable distribution over a particular interval I=[a,b]
I am trying to find the area over the interval I=[a,b] for a stable distribution. As you know, in general, the densities of stable laws do not have explicit expressions via elementary functions. ...
1
vote
1answer
190 views
Distributions that being to domain of attraction of a stable law that are not unimodal?
I was wondering whether there are any distribution that belongs to the domain of attraction of a stable law that is not unimodal. It is known that distribution in that law converge to a stable ...
0
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0answers
645 views
What options are there to 'normalize' values from a heavy-tailed distribution?
We have some data collected acquired from a complex setup, that is expected to come from a "fairly normal" underlying distribution. However when I investigate the data it appears that it's fairly ...
2
votes
1answer
210 views
What is the heaviest tail possible for a continuous normalizable distribution?
The heaviest tailed smooth normalizable continuous distributions that I am familiar with are those with fat power-law tails $\frac{1}{x^{1+\alpha}}$, e.g. a Pareto with $\alpha\rightarrow 0^+$ or a ...
1
vote
0answers
78 views
What is the necessity of log concave/ convex for tail distributions?
What is the impact of log concave density for light tailed distribution? How it could be substantiated with real time example?
Most of the books and research papers highlights that a distribution ...
5
votes
3answers
533 views
Fat tail? Short tail? Long tail? Where do I go from here?
I am running a linear mixed model with 4 fixed factors and 1 random factor. The response variable is %growth and it has negative values (some of my animals shrunk). The problem I'm having is the ...
1
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1answer
256 views
Bounding tail probabilities of the Poisson Binomial Distribution?
In a problem I'm working on, I have Bernoulli random variables $X_1,X_2,\dots,X_k$ ($k$ is odd) and I am interested in their sum $Y = \sum_{i=1}^k X_i$. In this problem, $P(X_i=1) = p_i$ and $P(X_i=0) ...
2
votes
0answers
127 views
definition of Black swan random variables
What's the precise mathematical definition of a black swan random variable?
Taleb describes it approximately here(http://highlands.vmhost.psu.edu/_reading/docs/blackswan.pdf), where he describes ...
1
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0answers
2k views
Difference between light tail and heavy tail distribution [duplicate]
I read numerous websites including wikipedia on heavy and light tail distributions. However, I am not quite understanding the distinction between the two. In some sources, it notes that light tail ...
4
votes
1answer
140 views
Besides the Pareto and Zipfian distributions, which distributions obey the power-law?
I need a list of distributions that obey the power-law, beside the commonly used Pareto and Zipfian distributions. A comprehensive list or a reference to a comprehensive list will be particularly ...
0
votes
2answers
282 views
A Tail Bound For Poisson Binomial Distribution?
Consider the Poisson-Binomial Distribution with two components. Let $Y_0\sim bin(n,p_0)$, $Y_1\sim bin(n,p_1)$, and let $Y=Y_0+Y_1$. For any $k>n(p_0+p_1)$,
Can we upper bound the tail probability ...
1
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0answers
187 views
which percentiles can be used to better describe the tail distribution
I understand that the extreme value distribution is concerned about the density of the tail which describes the losses if I am not wrong.
In such a case which part of the density(expressed as ...
5
votes
1answer
1k views
How is the tail of a distribution defined (about heavy-tailed distributions)?
Some distributions are said to be heavy-tailed. It seems that one definition of a heavy-tailed distribution is that its tails are heavier than the tails of an exponential distribution. However, how ...
1
vote
1answer
101 views
Tail equivalence for heavy-tailed data
Is it possible for a distribution $F(x)$ that has not a Pareto ($G(x)$) right tail equivalence to fit well heavy-tailed data?
That is, to have ${\lim_{x\rightarrow\infty}}\frac{1-F(x)}{1-G(x)}=0$ ...
2
votes
2answers
2k views
Linear Regression with heavy tailed noise
The model is linear $y_i = a\cdot x_i + b + e_i,~ i = 1,2,\ldots,N $. It is given that the noise is heavy tailed. However the distribution of noise conditional on $x$ is the same for all data points. ...
2
votes
1answer
88 views
Fractional moments of the Laplacian distribution larger than of the normal
How can I show that the fractional moments of the (unit variance) Laplacian distribution are higher than of the standard normal distribution, for moments higher than 2?
Formally, if $l \sim Laplace(...
-1
votes
1answer
2k views
Best transformation for a heavy tailed distribution
I am anaylsing a data set, which displays a heavy-tailed distribution when examined on a Quantile-Quantile plot. What is (or are) the best transformation(s) to use to correct a dataset with a heavy-...
2
votes
1answer
442 views
How are errors terms calculated in GARCH model by rugarch package?
I am fitting a GARCH(1,1) model to the data and want to look at the innovation distribution.
...
2
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0answers
104 views
Predictive modeling of an complex panel of heavy-tailed data
I am struggling to develop a sensible strategy or protocol for the predictive modeling of a complex set of data. Apologies in advance for the indeterminate nature of some of this description but it’s ...
0
votes
2answers
492 views
Data transformation for heavy tailed data for mixed model use
I am trying to transform my data to meet assumptions of a mixed model (lme4). This is the qqplot for the data.
I have tried the traditional transformations: log & square root.
4
votes
3answers
935 views
Are two asymptotic values enough to fail the test of normality?
Looking at this post I started to wonder about the gestalt interpretation of the QQ plots generated by qqnorm in R. Here's the plot to avoid having to go to the ...
6
votes
1answer
598 views
Bernstein's inequality for heavy-tailed random variables
It is known that for independent sub-exponential random variables, the following Bernstein-type inequality holds:
\begin{align}
\mathbb{P}\biggl(\biggl| \sum_{i=1}^N a_i X_i\biggr| >t \biggr) \...
8
votes
3answers
5k views
t-distribution having heavier tail than normal distribution
In my lecture notes it says,
t-distribution looks like normal, though with slightly heavier tails.
I understand why it would look normal (because of the Central Limit Theorem). But I am having ...
