A random variable or stochastic variable is a value that is subject to chance variation (i.e., randomness in a mathematical sense).

learn more… | top users | synonyms (1)

12
votes
3answers
231 views

Uniform random variable as sum of two random variables

Taken from Grimmet and Stirzaker: Show that it cannot be the case that $U=X+Y$ where $U$ is uniformly distributed on [0,1] and $X$ and $Y$ are independent and identically distributed. You should not ...
0
votes
0answers
13 views

Relation of distributions

I want to predict a distribution using multiple related distributions. One method is to use multiple regression (the model specification is that the dependent variable, yi is a combination of the ...
4
votes
1answer
43 views

Do these random variables satisfy Lindeberg's condition?

I have the followig sequences: $Pr(X_n=n)=Pr(X_n=-n)=0.5$ $Pr(X_n=2^{n/2})=Pr(X_n=-2^{n/2})=0.5$ I have to show whether they satisfy Lindeberg's condition or not, but this condition is a bit ...
1
vote
0answers
17 views

How to simulate a random variable from a matrix variate distribution?

I am trying to simulate a random variable from the matrix variate normal distribution but have not seen any literature on it. If somebody could point me in the right direction for that or if they ...
0
votes
0answers
16 views

Matlab: How to implement inverse of determinant of covariance-variance matrix [on hold]

I have asked this Question http://stackoverflow.com/questions/27068927/matlab-variancecovariance-matrix and repeating it here because I am unsure where it will probably get an answer. When solving ...
1
vote
2answers
44 views

Transform two correlated random variable to independent variables without knowing correlation

I am thinking about this interesting question which arises in the following realistic setting. For example, in one medical experiment one drug and one placebo are applied to two randomized groups of ...
0
votes
0answers
18 views

Fast way to compute central moments of a Poisson random variable?

I am looking for a way to quickly compute the central moments of a Poisson random variable. I've found a couple of resources on how to compute the central moments, but I'm still trying to figure out ...
-1
votes
0answers
10 views

Estimator for a function depending on a random variable [duplicate]

Let $X$ be random variable in $m$ dimensional space. The distance between each pair of vectors $x_i^m,x_j^m$ is $D_{i,j}^m =d(x_i^m,x_j^m)$. Correlation Sum, $C(r)$ represents the probability of the ...
0
votes
0answers
9 views

Decomposition of a random vector into uncorrelated components

I have a set of random vectors $Y_i$ and their correlation matrix $C_{i,j}$. Each vector can be thought of as a sum of two uncorrelated vectors $Y_i=A_iX+B_iY$, where $X,Y$ are the same vectors for ...
2
votes
1answer
22 views

Properties of the minimum of several random variables

I've come across an interesting problem in my research that I don't quite know the answer to. Suppose I have a bunch of random variables: $$ X_1, X_2, X_3, ... X_N $$ They are not identical but they ...
6
votes
1answer
85 views

Random variables with some properties (conditional expectation)

I am looking for two random variables which fulfills the following two things: a) $\mathbb E(X|Y)<\infty$ and $\mathbb E(Y|X)<\infty$ b) $E(X|Y)> Y$ and $\mathbb E(Y|X)>X$ a.s Here is ...
0
votes
0answers
29 views

Using lmer for random effect and nested interpreting model comparison

I'm trying to do a lmer in r. I did an experiment in which I manipulated the temperature. My dataframe contains the following factors: Site: 11 level, random Species: 2 levels, fixed Subject: 10, ...
0
votes
1answer
16 views

MSE decomposition to Variance an Bias Square

In showing that MSE can be decomposed into variance plus the square of Bias, the proof in wikipedia has a step, highlighted in the picture. How does this work? How is the expectation pushed in to the ...
2
votes
2answers
52 views

Derive the LLN for a certain sequence

I have a sequence of dependent random variables $X_1, X_2...X_n$. Each RV is correlated with two other RVs and uncorrelated with the others.The ones that are correlated satisfy the condition ...
1
vote
0answers
29 views

What is the distribution of these functions of Nakagami random variables?

I am new to this forum and hope I can get help. A Nakagami random variable $X$ with parameter $m$ has the following pdf $$X\sim \frac{2m^m}{\Gamma(m)\Omega^m} x^{2m-1}e^{-\frac{m}{\Omega}x^2}$$ ...
0
votes
1answer
13 views

Prevalence estimates based on randomized sample of clinical data

This is probably one of the more straight forward questions on here but here it is: I want to use a random number generator to sample X number of charts to look for the # occurrences of Y event. So ...
2
votes
0answers
20 views

asymptotic covariance between mean and standard deviation

I am trying to estimate the asymptotic covariance between mean and standard deviation. I know the following $$\sqrt n \hat \mu \xrightarrow{d}N\left( {\mu ,{\sigma ^2}} \right),\sqrt n \hat \sigma ...
0
votes
1answer
39 views

Example for uncorrelated, not independent , but with same distribution functions random variables

I am looking for an example of two random variables X and Y on $\Omega=\{-2,-1,0,1,2\}$ with the following properties: a) X and Y have the same distribution b) X and Y are uncorrelated c) X and Y ...
1
vote
0answers
73 views

Exponential random variable

The time it takes a printer to print a job is an exponential random variable with mean of 10 seconds. You send a job to the printer at 9:00 am, and it appears to be the fourth in line. What is the ...
2
votes
0answers
39 views

Sum of Bernoulli random variables

I need some help with a homework assignment. The question I'm given is: "Suppose that $X_1, X_2,..., X_n, W$ are independent random variables such that $X_i\sim Bin(1,0.4)$ and $P(W=i)=1/n$ for $i=1, ...
0
votes
1answer
62 views

How to bound a probability with Chernoff's inequality?

In my class, we were given Chernoff's inequality as $$P(X\le -t) \le e^{(-(\lambda*t - \log( E(e^{-\lambda*x}))))}$$ $$P(X\ge -t) \le e^{(-(\lambda*t - \log( E(e^{\lambda*x}))))}$$ It says that to ...
4
votes
2answers
78 views

Expectation of $(X + Y)^2$ where $X$ and $Y$ are independent Poisson random variables

I would really appreciate anyone's help with this problem: (let $E$ denote expectation) Suppose $X$ and $Y$ are independent Poisson random variables, each with mean $1$. Find: $E[(X + ...
0
votes
1answer
22 views

Sum of dependent R.V

I have two random variables whose PDF are parameterized by an unknown constant as follows: P(A;d) P(B;d) apparently, these two are not independent, so to find P(A+B;d) one cannot use convolution. ...
0
votes
1answer
46 views

sum of correlated random sample

Suppose I have 1000 draws each of two random variables X and Y. If I wanted to sample the sum of these variables, I would simply calculate 1000 samples, i.e. $$ S_{i}=X_{i}+Y_{i}, i=1,2,…,1000 $$ ...
0
votes
0answers
13 views

G and R matrices in mixed model and model selection

I have data in which the plants were subjected to four conditions and measured weekly for a month. I would like to incorporate "plot" as a random factor into my linear mixed model using SPSS. I am ...
0
votes
1answer
46 views

Covariance of a compound distribution

I am trying to find the covariance of a compound distribution. Given $X=x$, where $X \sim \mathrm{Uniform}(0,1)$, $Y$ is (conditionally) normally distributed with mean $x$ and variance $x^2$. I ...
0
votes
1answer
35 views

Bayesian Network

I am preparing for midterm exam and need to know what is the step by step solution to this question? Answer is shown in red. Also any external related link is very much appreciated.
1
vote
2answers
96 views

How to prove dependence of random variables

I need to solve the following problem. Let $X$ be a normal random variable with mean $\mu$ and standard deviation $\sigma$ and let $I$, independent of $X$, be such that $\mathbb{P}(I = 2) = ...
0
votes
0answers
15 views

Convergence of Random Variables meaning

What is the intuitive explanation of convergence of random variables? what is meant by saying that a sequence of random variables CONVERGE?
1
vote
1answer
26 views

Sequence of Random Variables

I am confused about how to approach sequence of random variables that are not identically distributed. For example, consider a sequence $X_1, X_2, \dots, X_n$ with the pdf: $$ f(X_n)= \begin{cases} ...
1
vote
0answers
26 views

Sampling from a distribution with a margin of error

A survey of a population is taken using sampling. It is determined that 70% prefer option A and 30% prefer option B with a margin of error being 5%. Normally when simulating the process with the ...
1
vote
0answers
23 views

Number of trials to observe all values of a uniform discrete random variable X with a probability of at least 1-q?

Let X take on p values with equal probability. If n trials are to be conducted to ensure that the probability of not observing any of these p values is less than or equal to q, what is the value of ...
0
votes
0answers
19 views

Linear Combination of Random Normal Variables

In order to prove that the linear combination of two independent normal distributions(say Z=X+Y) is normal, i am using their MGFs to show that the linear combination also has a similar mgf. This works ...
1
vote
0answers
42 views

Distribution for $Y = \sqrt{X_1^2 + X_2^2}$, when $X_1, X_2$ are dependent and normally distributed with different variance? [duplicate]

Is there a closed form distribution for the transformation given by $Y = \sqrt{X_1^2 + X_2^2}$, when $X_1, X_2$ are jointly normal but dependent random variables with different variance? OBS: I know, ...
2
votes
1answer
64 views

Combination of Random Variables Conditional Probability

If A and B are independent discrete random variables and C = A+B, then how should one compute the pmf of P(A|C)? For example, let X be the result from a coin toss(1 or 0 for H and T) and Y be the ...
1
vote
1answer
37 views

Probability distribution, unfair coin

An unfair coin which has 0.35 probability to result head is tossed four times. Build and represent graphically the probability distribution and the cumulative ...
2
votes
0answers
37 views

Are matrix Fisher r.v.s closed under multiplication?

With appropriate parameters, a matrix Fisher distribution provides a distribution over SO(3) (i.e. over rotations in $R^3$). See this MathOverflow post for a few notes describing the distribution. ...
1
vote
1answer
38 views

Can an a.s. (almost surely) finite random variable be a.s. UNbounded?

I thought that if a random variable, $\eta^2$, is assumed to be a.s. finite, then $\eta^2$ must be a.s. bounded. In the Martingale Central Limit Theorem in Hall & Heyde, they assume this: "let ...
2
votes
1answer
97 views

Moment Generating Function of a nonlinear transformation of an exponential random variable

Let $\tau$ be an exponential random variable, with parameter $\lambda$. Let $$ V = \delta^\tau $$ where $0 < \delta <1$. Sorry if this notation seems strange, but it is what I am using, I ...
1
vote
0answers
32 views

How to find the significantly different groups in Random Effects

I am using a mixed effects model as created here (using dummy data for now) in this R script ...
4
votes
2answers
122 views

Calculate $\mathbb{E}[Z_i]$ where $Z_i = \min(X_i, Y_{i-1})$, $X \sim Beta(\alpha,1)$

Let $X$ be a IID random variable with support in $[0,1]$ and CDF given by a Beta distribution, i.e. $X \sim \mathrm{Beta}(\alpha,1)$. Let $Z_i = \min(X_i,Y_{i-1})$, $\forall i >1$. I would like to ...
2
votes
1answer
46 views

Sum of Random Variables

As part of my statistical mechanics class, I'm trying to go through Kardar's statistical physics of particles and I'm having trouble with this one line: Consider the sum $X=\displaystyle ...
2
votes
2answers
98 views

Skewness of a random variable that have zero variance and zero third central moment

If I have a random variable $x$, and the only information I know about it are: $$ m_1=E[x]=c, \mu_2=var(x)=0, \mu_3=E[(x-m_1)^3]=0$$ Can I conclude that the function distribution is symmetric about c? ...
2
votes
1answer
39 views

How is this Negative Binomial Random variable used to solve this problem?

I was looking at the solution to this problem below and I don't understand how they used a negative binomial R.V. to solve the problem. A research study is concerned with the side effects of a new ...
4
votes
1answer
199 views

Do mean, variance and median exist for a continuous random variable with continuous PDF over the real axis and a well defined CDF?

For a continuous random variable with continuous PDF over the real axis and well defined CDF, are the mean, variance, and median always well defined? Mean and variance do not always exist, e.g. for a ...
0
votes
1answer
318 views

Expected Value of Random Variable

I'm trying to find the expected value of a random variable $t_i$ which is the solution of $$\epsilon_i=\mu(t_i-t_{i-1})-\sum^{i-1}_{k=1}\frac{\alpha}{\beta}\left(1-e^{-\beta(t_i-t_k)}\right)$$ ...
2
votes
1answer
39 views

Does the average of the square roots of random variables mean anything?

I recently made a plot for work that used a signed square-root scale on the $y$ axis, for visual clarity. The $y$ observations are impulse response functions (IRF) of vector autoregressions computed ...
0
votes
0answers
10 views

probability life similarities in a population cross section

I have just read up on Bouchard's Minnesota Twins study that turned up some amazing identical similarities in the lives of some identical twins reared apart. Both had same jobs, married and divorced ...
0
votes
1answer
28 views

Random variable variance

I have the model $y_i=\beta_1+\beta_2 X_i+ u_i$ where $u_i\sim\text{iid } N(0,\sigma^2)$. I estimate $\beta_1$ and $\beta_2$ by drawing a straight line between the first $(x_1,y_1)$ and last dot ...
6
votes
0answers
129 views

Applying a variance-stabilizing transform to a fitted function (rather than data)

Outline I'm working with data corrupted by a mixed Poisson-Gaussian noise model (for example with images gathered in astronomy or electron microscopy), and have been using the generalized Anscombe ...