Register to reply 
Proof of the Weak Law of Large numbers by using Moment Generating Functions 
Share this thread: 
#1
Jan212, 08:37 AM

P: 118

1. The problem statement, all variables and given/known data
I need a thorough proof of the weak law of large numbers and it must use moment generating functions as below. 2. Relevant equations The weak law of large numbers states that given X1.....Xn independent and identically distributed random variables with mean μ and variance σ^{2} then X = (1/n) * Ʃ Xi tends to μ in distribution as n > ∞ I am required to start with showing E[e^{θX} ] → e^{θμ} as n→∞ 3. The attempt at a solution This is what I have done. E[e^{θX} ] = E[e^{θ*(1/n) * Ʃ Xi} ] E[e^{θ*(1/n) * Ʃ Xi} ] = Product of E[e^{θ*(1/n)*Xi} ] from i = 1 to n Since the random variables Xi are independent and identically distributed i can just consider the moment generating function of X1, I know that [itex]\varphi[/itex]x1 (θ/n) = (1 + θμ/n + E[X1^{2}]θ^{2}/n^{2}) By the taylor expansion of mgf up to order 1 So now E[e^{θ*(1/n) * Ʃ Xi} ] = (1 + θμ/n + E[X1^{2}]θ^{2}/n^{2})^{n} And so Log( E[e^{θ*(1/n) * Ʃ Xi} ]) = nLog((1 + θμ/n + E[X1^{2}]θ^{2}/n^{2})) = n(θμ/n + E[X1^{2}]θ^{2}/n^{2}) By using Log(1+x) = xx^{2}/2 ... = θμ + (E[X1^{2}]θ^{2}/n ) → θμ as n→∞ Is this correct? 


Register to reply 
Related Discussions  
Moment generating functions  Set Theory, Logic, Probability, Statistics  2  
MomentGenerating functions  Calculus & Beyond Homework  1  
Moment Generating Functions  Calculus & Beyond Homework  17  
Moment Generating Functions and Probability Density Functions  Set Theory, Logic, Probability, Statistics  4  
Weak Law of Large Numbers versus Central Limit Theorem  Set Theory, Logic, Probability, Statistics  12 