Questions tagged [discrete-distributions]

The tag has no usage guidance.

Filter by
Sorted by
Tagged with
2
votes
1answer
20 views

Convolution of probability mass functions (3 non-parametric distributions)

I am familiar with the convolution of probability mass function when it involves two random variables, but I get a little confused when there's a third one. I have to find the probability mass ...
1
vote
1answer
25 views

Can we always write a random variable as conditional expectation plus error?

Consider the random variables $Y,X$. I believe that we can always write $$ Y=E(Y|X)+\epsilon $$ with $E(\epsilon|X)=0$. Question: Is the above true regardless whether $Y$ is a discrete or continuous ...
0
votes
1answer
47 views

Sufficient Statisitics and Discrete Distributions

I am trying to master minimal/complete sufficient statistics, however I am having trouble when the distributions are discrete and involve indicator functions. Here is my 3 part question: Let $X$ be a ...
2
votes
1answer
47 views

Parameterized probability distribution for finite, discrete values?

Sorry if I don't have the right terminology for asking this question in a good way ... I'm curios if there is an established distribution function for the following case: I have 20 different options, ...
5
votes
4answers
121 views

If $X$ and $Y$ have the same marginal distribution, then do they have to have the same conditional distribution?

Suppose $X$ and $Y$ are two random variables that have the same distribution. Does $$P[X \leq t \mid Y=a]$$ be necessarily equal to $$\;\ P[Y \leq t \mid X=a]?$$ Note that if $X$ and $Y$ are bivariate ...
0
votes
0answers
29 views

joint PDF of continuous and discrete random variables

Given exponential a random distribution X with PDF $f_X(x)=\lambda e^{-\lambda x}$ and a random variable Z with the PMF $p_Z[z]=0.5, z= \pm1$, I am trying to find the PDF of $Y=ZX$ (I also know that Z ...
7
votes
2answers
91 views

Let $X,X_1,X_2,X_3,…$ be positive integer random variables. Show that $X_n \overset{d}{\to} X$ implies $\lim_{n\to\infty} P(X_n=k) = P(X=k)$

Question Let $X,X_1,X_2,X_3,...$ be positive integer random variables. Show that $X_n \overset{d}{\to} X$ implies $\lim_{n\to\infty} P(X_n=k) = P(X=k)$. The $\overset{d}{\to}$ denotes convergence in ...
0
votes
0answers
34 views

Generating correlated discrete random variables

Suppose that we have $q_t \in \{-1, 1\}$ where $\mathbb{P}(q_t = -1) = \mathbb{P}(q_t = 1) = \frac{1}{2}$. Further, assume that \begin{align} Cor\left( q_t, q_{t-k} \right) = \begin{cases} ...
3
votes
1answer
76 views

Sufficient Statistics and Discrete Distributions

Let $X_1, \ldots, X_n$ be a random sample of size $n$ from the following distribution: $$f(x;\theta) = \left\{\begin{array}{ccc} \frac{1 - \theta}{6} & , & x = 1 \\ \frac{1 + \theta}{6} & ,...
3
votes
1answer
73 views

Conditional expectaction with probabilities for a sum of independent random variable

I have a r.v $S_N$ built as a sum of Bernoulli with parameter $p$. So $S_N = X_1 + X_2 + \ldots + X_N$. There is a second variable N, such that $N \sim Poisson(\lambda) $. I have to compute: $P(S_N=0)...
2
votes
0answers
15 views

Maximum entropy discrete distributions with specified mean

Consider a discrete distribution on {1, ...,n}, with mean given as $m$, what is the maximum entropy distribution? I know it takes the form $p_{X}(k)=ar^{k}$ and is a geometric distribution when n is ...
0
votes
0answers
23 views

In poisson distribution why does setting r = mean_value not output 50%?

If I want to find probability of 10 cars passing highway checkpoint in 60 seconds where on average 10 cars pass in 60 seconds. Assuming there is no rush hour I can use Poisson distribution So lambda =...
3
votes
2answers
149 views

Do financial return series have a probability mass function (pmf)?

Stock returns, computed from stock prices as $r_t = \ln (p_{t}) - \ln (p_{t-1})$, are real-valued and unbounded giving the impression that they are continuous random variables. But aren't they ...
0
votes
0answers
20 views

If $Y$ is continuous and $X$ is discrete, how to write the joint density of $(Y,X)$?

If $Y$ is continuous and $X$ is discrete with a finite number of points in the support, how to write the joint density of $(Y,X)$? For example, to write the joint density function evaluated at $(Y,X)=(...
1
vote
1answer
95 views

intuition behind Brier score

Assume that we have some count data $x_{1}, \dots, x_{n}$, which take values $\{1, \dots, m\}$ and we have some estimator of the probability mass function, $\hat{\mathbf{p}} = (\hat{p}_{1}, \dots, \...
0
votes
0answers
12 views

Are discrete maximum entropy distributions uniquely determined by their energy function?

I read this somewhere but can't find a reference, I'd love to be pointed in the right direction. I'm specifically interested in discrete Boltzmann distributions with interactions at different orders, ...
0
votes
1answer
47 views

guessing a number between 1 and 100

Person A chooses an integer between 1 and 100 at random, then B can guess that number in (at most) 7 attempts, i.e. $\log_2(100)+1=7$. What if now A chooses an integer from a distribution that is ...
2
votes
2answers
74 views

Is there a discrete distribution I can use for sampling in R?

Firstly, I don't have a stats background, so please accept my apologies for any errors or misunderstandings in the question below. I'm trying to use R to draw values from a discrete probability ...
1
vote
2answers
66 views

How to know whether a zero-inflated model is the way to go? Both poisson and negative binomial do not fit my count data

I have a dataset with count data as response variable ranging from 0-5 (number of chicks fledged). I intend to carry out a GLMM and need to know which distribution my data follows. I used the descdist(...
2
votes
1answer
36 views

Intuition for expectation of discrete random variable that takes positive integers

If $X$ is a discrete random variable that takes values on the positive integers, it is true that $$E(X) = \sum_{k=1}^{\infty} P(X \ge k)\;.$$ I know how to prove this (by expressing the summand as a ...
4
votes
2answers
136 views

Sampling distribution of the mean of the discrete-power law distribution

For a certain problem I wish to generate random integers $k$ so that their distribution follows $p_k \sim k^{-\alpha}$ for $k \geq k_{\text{min}}$, $k_{\text{min}} > 0$. I am following the ...
4
votes
3answers
106 views

Distribution of X+U when X is a discrete and U is a continous random variable

Suppose $X$ and $U$ are independent random variables. $X$ is a discrete uniform variable and $U$ is a continuous uniform $[0,1]$ variable. What is the value of $\mathbb P(X+U\leq y)$, where $y$ is a ...
1
vote
1answer
20 views

Error on the mean for discrete histogram

Suppose I have a discrete histogram, in this case the number of votes for each rating (1-5 stars) for a product. I can calculate the sample mean easily enough, and get an average score for this ...
0
votes
0answers
31 views

Maximum-likelihood histogram from noisy data

Given a sequence of noisy observations $\{x_k\in\mathbb{R}\}$ and a set of thresholds $\{t_i\in\mathbb{R}\}$ we can bin the observations using the thresholds to create a histogram. However, since we ...
0
votes
0answers
30 views

Approximating a distribution with an integer histogram

Given a distribution $f:[0,a)\rightarrow\mathbb{R}$, is there a simple algorithm by which to find a sequence $\{h_i\in\mathbb{N_0}\}$ such that $f(x)$ is approximated by $h_{floor(x)}$ as a histogram ...
0
votes
0answers
29 views

Factorial moment bound for discrete Binomial distribution

I need to compute the upped bound for the tail (survivor) probability $P(X \ge t)$ for the discrete Binomial random variable $X$. I could use Chernoff bounds, however according to this paper [1] the ...
0
votes
1answer
62 views

Bayes test function with a discrete prior

Let X be exponential with mean θ. Consider testing H0 : θ = 1 versus H1 : θ = 2 with a single observation. Loss function: 0-1 Loss function. So the risk of the test function φ is R(1, φ) = E1 (φ(X))...
0
votes
0answers
11 views

What are the limmitations of reparametrization gradients for discrete random variables? (Gumbel-softmax)

We know that one approach for re-parametrizing gradients for variational inference is taking the Gumbel-softmax estimator proposed in [1] and [2]. In [3], that is a talk on SVI, D. Blei at around 29:...
1
vote
1answer
45 views

How to plot density for repeated k-fold cross validation?

Long story short, I conducted regression using repeated k-fold cross validation. While messing around I decided to plot the density of the R-squared distribution for the resampling. Obviously there ...
0
votes
1answer
35 views

Textbook probability question - is this unrelated data to throw you off?

4.24 from Newbold 8th Edition: The probability of a team winning a game is 0.45. What is the probability that the team will: a) win 2 games out of 5; b) win 10 games out of 25? If the ...
2
votes
2answers
27 views

Number of draws required to draw a given number of special objects in SRSWOR

Suppose we have a set of $N$ objects with $K$ special objects of interest. We draw from our set of objects using simple random sampling without replacement (SRSWOR), and we are interested in ...
3
votes
1answer
31 views

Looking for a discrete distribution with a specific mean-variance relationship

Say we have some counts $Y$ for which the mean-variance relationship is $$ Var[Y] = \alpha E[Y] + \beta E[Y]^2. $$ From this, we can say that: If $\alpha = 1$ and $\beta = 0$, then $Y$ can be ...
2
votes
2answers
31 views

What is the probability that the third largest value of 39 rolls with a 9-sided dice is 8?

If I have 39d9, that is 39 rolls with a 9-sided (fair) dice, what is the probability that the third-largest value of all the rolls is an 8? I know there are some specific situations where this is ...
2
votes
1answer
55 views

Mathematical Statistics (Wackerly, Mendenhall, Scheaffer): Problem 4.98: Mixed Probability Distribution

Problem Statement. The duration $Y$ of long-distance telephone calls (in minutes) monitored by a station is a random variable with the properties that $$P(Y=3)=0.2\qquad\text{and}\qquad P(Y=6)=0.1.$$ ...
7
votes
4answers
586 views

How to interpret sum of two random variables that cross domains?

suppose we have two discrete random variables: $X: \{$6 sided dice rolls$\}$ $\rightarrow \{1..6\}$ (following uniform distribution) $Y: \{$coin flips$\}$ $\rightarrow \{0,1\}$ (following uniform ...
2
votes
0answers
42 views

Measure how good is the discrete approximation of continuous random process?

If continuous random random process approximated with discrete version - how to measure how good is the approximation? One possible way is to compute and compare the moments. But for some probability ...
1
vote
1answer
32 views

Can the pdf of the difference of two independent random variables be found out using their Probability Generation Functions?

I recently learned of probability generation functions and that the sum of two independent random variables can be found out by multiplying the PGFs. I wanted to know if anything similar can be done ...
1
vote
1answer
92 views

Using one-sample Kolmogorov-Smirnov test impementation for comparing two samples with purely discrete CDF

In one-sample Kolmogorov-Smirnov test one tests whether sample $X = (X_1,\dots,X_n)$ come from theoretical distribution by computing $D_n = \sup_{x} |F_n(x) - F(x)|$, where $F_n(x)$ denotes the ...
1
vote
2answers
44 views

Estimation of Discrete random variables

Suppose you have a discrete random variable $X_1$ with known probability mass function. I guess that choosing a variable drawn from the same pmf would be the best way to guess $X_1$ assuming all ...
1
vote
1answer
26 views

Categorical sampling without instantiating probability vector

I want to sample from a discrete distribution with probability vector $p \in \mathbb R^n$, where $n$ is large. Suppose that $p_i = f_i / Z$, where $Z$ is a normalization constant. I can compute the ...
1
vote
1answer
204 views

How to solve for the minimum KL Divergence when the distribution is discrete?

Say we have a simple case of $p(x,y)$ is a 3x3 matrix: $$\begin{bmatrix} 1/6 & 0 & 0 \\ 1/6 & 3/6 & 0 \\ 0 & 0 & 1/6 \end{bmatrix}$$ And $q(x,y)=...
4
votes
1answer
77 views

The meaning of a parameterization of the logarithmic distribution

In calculus one learns that $$ p + \frac{p^2} 2 + \frac{p^3} 3 + \frac{p^4} 4 + \cdots = -\log(1-p). \tag 1 $$ Thus a discrete probability distribution on the set $\{1,2,3,\ldots\}$ is given by $$ \Pr(...