Consider the default statistical model, where Y stands for the popula-tion and its distribution stands for...
Let Y1, Y2, ..., Yn be independent random variables each having
uniform distribution on the interval (0, θ).
Find variance(Y(j) − Y(i))
Let Yİ,Y2, , Yn be independent random variables each having uniform distribu - tion on the interval (0,0) Fin ar(Y)-Yo
Let Y1, Y2, ..., Yn be independent random variables
each having uniform distribution on the interval (0, θ).
(a) Find the distribution of Y(n) and find its expected
value.
(b) Find the joint density function of Y(i) and Y(j) where 1 ≤ i
< j ≤ n. Hence
find Cov(Y(i)
, Y(j)).
(c) Find var(Y(j) − Y(i)).
Let Yİ, Ya, , Yn be independent random variables each having uniform distribu- tion on the interval (0, 6) (a) Find the distribution...
Suppose Y1, Y2, …, Yn are independent and identically distributed random variables from a uniform distribution on [0,k]. a. Determine the density of Y(n) = max(Y1, Y2, …, Yn). b. Compute the bias of the estimator k = Y(n) for estimating k.
Let Y1, Y2, . .. , Yn be independent and identically distributed random variables such that for 0 < p < 1, P(Yi = 1) = p and P(H = 0) = q = 1-p. (Such random variables are called Bernoulli random variables.) a Find the moment-generating function for the Bernoulli random variable Y b Find the moment-generating function for W = Yit Ye+ … + . c What is the distribution of W? 1.
1. Let Yi,Y2, ,y, be independent and identically distributed N( 1,02) random variables. Show that, EVn P( Y where ) denotes the cumulative distribution function of standard normal You need to show both the equalities
Let Y1, Y2, ..., Yn be independent random variables
each having uniform distribution on the interval (0, θ)
(c) Find var(Y(j) − Y(i)).
Let Y İ, Y2, , Yn be independent random variables each having uniform distribu- tion on the interval (0,0) Let Y İ, Y2, , Yn be independent random variables each having uniform distribu- tion on the interval (0,0)
2) Let Yİ,Ý,, ,y, be independent and identically distributed from the distribution with density where c > 0 is a constant and θ > 0. Find the MLE for 60.
2) Let Yİ,Ý,, ,y, be independent and identically distributed from the distribution with density where c > 0 is a constant and θ > 0. Find the MLE for 60.
9. Consider the following hidden Markov model (HMM) (This is the same HMM as in the previous HMM problem): ·X=(x, ,x,Je {0,1)、[i.e., X is a binary sequence of length n] and Y-(Y Rt [i.e. Y is a sequence of n real numbers.) ·X1~" Bernoulli(1/2) ,%) E Ip is the switching probability; when p is small the Markov chain likes to stay in the same state] . conditioned on X, the random variables Yı , . . . , y, are...
Statistical Linear Models.
Multivaruate Normal Distribution
For the conditional distributuon this is the
formula
Consider the random vector Y= where 0 1 0.2 0 0 1 Y-N 0.2 1 0 0 0 2 0.5| To 0 0.5 21/ Answer the following questions: (a) What is the distribution of the random variable Y + 2Y - Y? . (Y + 2Y - YA ion of (y + 2y + y) (c) What is the conditional distribution of (Y + 2Y2 -...
I don't understand a iii and b ii, What's the procedure of
deriving the limit distribution? Thanks.
6. Extreme values are of central importance in risk management and the following two questions provide the fundamental tool used in the extreme value theory. (a) Let Xi,... , Xn be independent identically distributed (i. i. d.) exp (1) random variables and define max(Xi,..., Xn) (i) Find the cumulative distribution of Zn (ii) Calculate the cumulative distribution of Vn -Zn - Inn (iii)...