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4 votes
1 answer
63 views

Convergence of an infinite sum of weighted independent and identically distributed random variable

Let $z_i$ be $i.i.d$ random variable with $E(z_i)=0$ and $E(Z_i^2)=1$ with a symmetric distribution. Further, $|\beta|<1$. Now consider $\sum\limits_{i=1}^{\infty} \beta^i (z_i+|z_i|)$. I want to ...
mathstat's user avatar
2 votes
0 answers
52 views

Numerical evaluation of infinite sums

I am working with Skellam random variables and I would like to evaluate the CDF of the absolute value of a Skellam random variable in which both Poisson random variables have the same rate, $\lambda_1 ...
Lewkrr's user avatar
  • 530
2 votes
1 answer
143 views

How to prove absolute summabilities implies the absolute summability of the product series?

In SHUMWAY 2017 Time Series Analysis and Its Applications with R examples 4E, page 486, it states: $\Sigma_{j=-\infty}^{\infty} |a_j| < \infty$ and $\Sigma_{j=-\infty}^{\infty} |b_j| < \infty$ ...
Erdogan CEVHER's user avatar
2 votes
1 answer
547 views

Why does absolutely-summable weights ensures a linear series itself summable (convergent)? Some questions on def'n of Linear Series

A "linear series" $y_t$ is the linear combination $$y_t - \mu = \sum_{i=-\infty}^{\infty}\psi_iL^i\nu_t = \sum_{i=-\infty}^{\infty}\psi_i\nu_{t-i}=S(L)\nu_t $$ of weighted (by $\psi_i$ weights) lags ...
Erdogan CEVHER's user avatar
2 votes
1 answer
1k views

Understanding the infinite sum of random variables

I am doing a course on time series analysis, and am struggling with this definition: We call a weakly stationary process $\{X_t\}$ invertible with respect to a white noise $\{\epsilon_t\}$ if ...
Henry's user avatar
  • 175
3 votes
1 answer
290 views

Can we show this sum of Gamma CDF converges, and if so can we derive its limit?

This is a bit of a strange question, but suppose I have some random variables. $$Y_i \sim Gamma(i,\lambda)$$ Where this comes from the fact that each $Y_i$ is defined as the sum of $i$ independent ...
Patty's user avatar
  • 1,779