Questions tagged [distributions]

A distribution is a mathematical description of probabilities or frequencies.

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Distribution of team sizes when splitting up a company at random

A monopoly has just lost an anti-trust case with the government, and will soon be broken into two smaller, separate companies. The former owners, bitter about this outcome, withhold the organisation's ...
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How to find the equal-weight mixture of an infinite set of probability distribution?

For example, the equal weight mixture of $p,q$ is $0.5p+0.5q$ Let $\Delta$ denote the convex hull. CASE1: The equal-weight mixture of the infinite set $\Delta(p,q)$ should be also $0.5p+0.5q$ CASE2: ...
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Expected deviation between a theoretical discrete probability distribution and the simulated one resulting from a number of trials

Suppose we have seven colors, each associated with a theoretical probability to choose one of them. The probabilities are as follows: red ______ 0.304761904761905 blue _____ 0.304761904761905 yellow ...
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Statistics Inference Question: "Prob(An equation) = 1" compared with "The equation holds" [duplicate]

When I study the textbook Statistical Inference by Casella and Berger, I have often seen expressions in the form of P(an equation) = 1. However, some other textbooks or lecture notes will instead say &...
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Is there a known distribution for event familiarity/novelty as a function of time?

As we go through life, we see fewer and fewer things for the first time. As time goes on, the events we encounter more often resemble events we've come across before. Picture a world where we somehow ...
Seán Healy's user avatar
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Mean of probability distributions? [duplicate]

Mean of a random variable $X$ is its expectation. I am interest in the new definition, mean of probability distributions Let $p,q$ be probability density distributions. $0.5p+0.5q$ is the mean ...
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Comparing distribution of a biomarker among patients with overlapping clinical features

I have a question how to compare the distribution of one tested biomarker among patients with different overlapping clinical syndromes. In my case, I am investigating patients with multiple sclerosis ...
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Solving equations where unknown parameters are distributions

Let $\mathcal{D}_1$, $\mathcal{D}_2$ and $\mathcal{D}_3$ be three distributions defined on some space $\mathcal{X}$. Assume $\mathcal{D}_1 = \mathcal{D}_2 + \mathcal{D}_3$ and $\mathcal{D}_1$ is ...
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What is the probability of group cohesion while admitting people into a nightclub at random?

A crowd of size $N$ outside a club is made up of $N/G$ groups of friends, for argument's sake, e.g. $G = 5$. This is a fictitious setup… groups are usually differing in size outside nightclubs… but ...
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How can I do valid tests simplification of a many-parameter distribution by consecutive parameter restrictions?

Suppose I have a data set that I believe is well-described as draws from a particular four- or five-parameter distribution, such as the Amaroso or the GB2. Some of those parameters can be made to ...
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What is the probability of selecting couples from a waiting room?

Given a waiting room, filled with $N / 2$ couples ($N$ an even number: the total number of people present in the waiting room), a doctor calls $n$ individuals from the waiting room at random. What is ...
Seán Healy's user avatar
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Maximum Likelihood Estimation for a Unique Probability Density Function

In the context of estimating parameters for a uniquely distributed set of independent and identically distributed random variables, I am examining the following probability density function $ f(x|\...
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On an infinite linear combination of chi-squared random variables

Question Let $Z_i\sim\chi_{(1)}^2$ be i.i.d. chi-squared random variables with 1 degree of freedom. We define: $$ W_{\infty} = \sum_{k = 1}^{\infty} \frac{Z_k}{2^{k}} $$ I have interest in computing ...
Luca Onnis's user avatar
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Why can a model's SHAP values change on a new dataset?

Background I'm validating a model and as part of the process I've been calculating SHAP values for different validation datasets. I've calculated SHAP values for every sample in each dataset taken ...
Connor's user avatar
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Metrics to assess the difference between two distributions [closed]

I'd like to assess the difference between two distributions and am a bit overwhelmed by the potential amount of metrics (see result of my preliminary search below). Is there a book / review paper ...
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How to show that the influence function of minimum density power divergence estimator with positive tuning parameter is bounded?

In the linked paper, in the influence function section, the term ${u_{\theta}(y)}{f_{\theta}(y)}^\alpha$ is directly called bounded which i do not get the explanation of? Here $\alpha > 0$ is the ...
Amlan Dey's user avatar
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What is the specific name of this distribution?

I just can’t seem to find the name of this distribution: $$\frac{e^{-x}}{(1+e^{-x}) ^2}.$$ From my understanding, it is generally applied to pandemics/epidemics. None of the statistics books that I ...
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Closed form expression for the 2-Wasserstein distance between generalized Gaussian distributions

Essentially the title - is there a closed form expression for the 2-Wasserstein distance (aka Frechet distance, Earth Mover's distance) between two generalized Gaussian distributions? The regular ...
Shashank Gupta's user avatar
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Example of a system with contextual statistics [closed]

What is a system described by a set of random variables for which there are distributions over subsets of these variables which are not marginal of a distribution over all random variables at once. ...
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Multinomial regression for modelling change of proportional makeup

I’m reaching the limits of my statistical understanding here when it comes to model specification in BRMS. I’m a PhD student researching how different drivers of species distribution (generalised into ...
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Concentration inequality for hypergeometric distribution

Let a population $C$ consist of $N$ values $c_1, c_2, \cdots, c_N$, with $c_i\in \{0,1\}$. Let $X_1, X_2, \cdots, X_n$ denote a random sample without replacement from $C$ and let $Y_1, Y_2, \cdots, ...
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Can i have a distribution that is not a marginal of another distribution?

Can there be a distribution that cannot be expressed as a marginal of some other distribution?
Khurshed Fitter's user avatar
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Does this type of distribution have a name?

I have some integer data, produced by slightly convoluted numerical procedure, which is distributed between $0$ and $300$, with the most probable values being $0$ and $300$, and the least probable ...
Tor's user avatar
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Sampling from a distribution characterized by its characteristic function

Consider the following measure: $$d\nu (x)=\mathbb 1_{(0,1)} (x) \frac 1 {x^{2}}$$ Now, define $X$ with characteristic function given by: $$\varphi_{X}(t)= \exp\left\{ \int_{\mathbb R} [e^{itx}-1 - ...
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Posterior Predictive Distibution [closed]

How do we actually calculate (what are the operations that need to be done) the posterior predictive given a vector of observations; can we do away with the assumption of independence? Let's say we ...
George Ntoulos's user avatar
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Species differential abundance across time series samples

Apologies if it is a stupid question or has been asked before or I have phrased it the wrong way, but I have been looking for an answer for days and I could not find anything - so any help will be ...
Panos Sapou's user avatar
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Can inverse sampling method be adapted to random vectors?

This might be a very basic question, but it seems that in all the examples I've seen, the inverse sampling method (i.e., input uniform RV into the inverse of CDF of desired PDF/probability ...
Fraïssé's user avatar
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5 votes
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expectation value, distribution function and the central limit theorem

The problem goes thus: ${\{X_n\}}$ is an $iid$ sequence of random variables with mean 0 and variance $\sigma^2$. If the third moment is finite, show that $$\lim_{n \to \infty} \mathbb{E} \left(\left(...
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How to identify popular items in time-series data

I have a dataset which contains time-series events in which each event is an item chosen from a unknowably large set of items. For example, let's say that the data entries are each music playlist ...
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Determine the distribution of a random variable

I want to solve the following A salesman has two different stores where he sells computers. The probability that he sells, in one day, a computer in the first store is $0.4$ and independently, the ...
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What is the resultant distribution of this two-step sampling process?

This is my sampling algorithm Let p(x) be a discrete distribution and f(x) be some function on real numbers. Consider $\textbf{Generate Samples from } p(x): \text{Initially, you sample } x_1, x_2, \...
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Distribution of a bootstrap sample from a given reference sample [duplicate]

Consider $n$ samples $X_1,X_2,..,X_n$, where each is normally distributed according to mean $\mu$ and variance $\sigma^2$. We use these samples to define our reference population. Given a bootstrap ...
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Probability of Random variable less than a quantity containing random variable [closed]

What is the probability of the following: $P\left(Z_j>\frac{\epsilon}{a_j*R}\left(\sum^{M}_{m=j+1} ~ a_m*R*X_m+1\right)\right)$ where $Z_j$ and $X_m$ are independent and identically distributed ...
learning statistics 's user avatar
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For KNN: How to justify that the probability of points to fall into a sphere of volume $V$ is $p(X)V$

https://www.cs.cmu.edu/~lwehbe/10701_S19/files/Lecture_3.pdf At the end of these notes, there is a short paragraph. Let $x$ be a test point. Let $x_1, \ldots, x_K$ be its $K$ nearest neighbors. Let $...
Shamisen Expert's user avatar
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What's the best clustering algorithm for Fraud Data?

Background I'm working on a Fraud dataset with 500,000 samples, and 130 features. There are: 98 numerical features, 32 categorical features, There are missing values in: 7 numerical features, 12 ...
Connor's user avatar
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3 votes
2 answers
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Approximating the distribution of the product of iid beta variates

Background I am interested in the distribution of $$\theta_0=1-\prod_{i=1}^n(1-\theta_i)$$ where the $\theta_{i>0}$ are iid beta random variates: $$\theta_{i>0}\sim\text{Beta}(\alpha,\beta)$$ In ...
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Comparing the output distribution of two ML models

Consider a regression task (e.g. predicting house prices) with a given train and test sets. We start with constructing a linear regression model, in which we assume $y_i=X^T\beta+\epsilon$ with $E[\...
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3 votes
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Calculating the cumulative distribution function and the probability density function of an interval with ratio of a shorter and longer segment

The interval $[0, 2]$ is divided into two parts by randomly marking a point in $[0, 1]$ according to the rectangular distribution. Let $X$ be the length ratio $L_1/L_2$ of the shorter segment $L_1$ to ...
Ste0l's user avatar
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1 vote
1 answer
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In a 2-arm clinical trial where ten centers recruited patients, how does one test that two distributions are statistically similar?

There are two arms in a clinical trial. If ten centers recruited subjects. How do I test in R that distribution across centers into two arms are statistically same? The distribution appears ...
abcihep's user avatar
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Methods for fitting a distribution to regression data

I'm hoping to find a method/algorithm/approach for fitting to a distribution to regression data. Essentially I have a problem where I have survival data with independent variables, but only cases that ...
VanDerGraaf's user avatar
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1 answer
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How to approach problem [closed]

I have a discrete random variable f(phi) with known probabilities for each n outcomes. Phi represents the random variables m parameters. Each parameter is its own independent discrete random variable ...
Help Plz's user avatar
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GLM: invalid value encountered in log special.gammaln

I've never used GLM before so I would like to have some hints on how to use it and if I'm missing any steps. My challenge: I want to know if the price of product is influenced, positively or ...
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Are there any research papers which show why Wasserstein distance is better than Jensen-Shannon/KL_div/Bhattacharya distance for specific use cases?

I am trying to find reliable research work which show why displacement based metrics such as Wasserstein distance is a better suited metric than Jensen-Shannon distance in specific use cases and for ...
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Estimating distribution function in a repeated measurement design

Suppose we have a repeated measurement design with imbalanced clusters so that $X_{1,1}, X_{1, 2}, \ldots X_{1, n_1} \sim F_1$, $X_{2,1}, X_{2,2}, \ldots, X_{2,n_2} \sim F_2$, and $ X_{m, 1}\ldots, ...
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How to measure the difference between two distributions of the same family?

Kullback-Leibler divergence seems to be a frequently used "metric" to measure the difference between probability distributions, regardless of their respective families. However, I would like ...
Value_Investor's user avatar
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Representation by Poisson transform

In physics papers that dealing with multiplicity distributions in high energy collisions, I have met with that some probability distributions can be expressed as a Poisson transform. See, eg., ...
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Hypothesis Testing - Varying p-value issue in my MWU

I have two machines (A & B) in our production line. A is older, B is very new. Both perform the same tasks, except that machine B is advanced and will perform 1 task less than the no of tasks in ...
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Is this the formula for the conditional covariance of normally distributed random variables? [duplicate]

Assuming $X$, $Y$, and $Z$ are normally distributed random variables, is it true that: $Cov[X, Y | Z] = Cov[X, Y] - Cov[X, Z]Cov[Y, Z] / Var[Z]$ Could you provide a simple derivation?
anonymous 's user avatar
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Choosing a probability distribution for 4D data: dirichlet challenges and alternatives

I'm seeking the right distribution for my 4D data, where the sum of values in each sample equals one. Currently, I've chosen to employ the Dirichlet distribution. However, upon applying this ...
roan's user avatar
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2 votes
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Pinsker-type inequality for moments?

Let $f_1$, $f_2$ be two discrete probability distributions. By Pinsker's inequality, the Kullback-Leibler divergence $D(f_1||f_2)$ sets an upper bound on the total variation distance between the two ...
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