Question

In: Statistics and Probability

The random variable X is distributed with pdf fX(x, θ) = c*x*exp(-(x/θ)2), where x>0 and θ>0....

The random variable X is distributed with pdf

fX(x, θ) = c*x*exp(-(x/θ)2), where x>0 and θ>0.

a) What is the constant c?

b) We consider parameter θ is a number. What is MLE and MOM of θ? Assume you have an i.i.d. sample. Is MOM unbiased?

c) Please calculate the Crameer-Rao Lower Bound (CRLB). Compare the variance of MOM with Crameer-Rao Lower Bound (CRLB).

Solutions

Expert Solution


Related Solutions

The random variable X is distributed with pdf fX(x, θ) = c*x*exp(-(x/θ)2), where x>0 and θ>0....
The random variable X is distributed with pdf fX(x, θ) = c*x*exp(-(x/θ)2), where x>0 and θ>0. a) Find the distribution of Y = (X1 + ... + Xn)/n where X1, ..., Xn is an i.i.d. sample from fX(x, θ). If you can’t find Y, can you find an approximation of Y when n is large? b) Find the best estimator, i.e. MVUE, of θ?
The random variable X is distributed with pdf fX(x, θ) = c*x*exp(-(x/θ)2), where x>0 and θ>0....
The random variable X is distributed with pdf fX(x, θ) = c*x*exp(-(x/θ)2), where x>0 and θ>0. (Please note the equation includes the term -(x/θ)2 or -(x/θ)^2 if you cannot read that) a) What is the constant c? b) We consider parameter θ is a number. What is MLE and MOM of θ? Assume you have an i.i.d. sample. Is MOM unbiased? c) Please calculate the Cramer-Rao Lower Bound (CRLB). Compare the variance of MOM with Crameer-Rao Lower Bound (CRLB).
The random variable X is distributed with pdffX(x, θ) = c*x*exp(-(x/θ)2), where x>0 and θ>0. (Please...
The random variable X is distributed with pdffX(x, θ) = c*x*exp(-(x/θ)2), where x>0 and θ>0. (Please note the equation includes the term -(x/θ)2 - that is -(x/θ)^2 if your computer doesn't work) a) What is the constant c? b) We consider parameter θ is a number. What is MLE and MOM of θ? Assume you have an i.i.d. sample. Is MOM unbiased? c) Please calculate the Cramer-Rao Lower Bound (CRLB). Compare the variance of MOM with Crameer-Rao Lower Bound (CRLB)....
2. Let X be a continuous random variable with PDF ?fx(x)= cx(1 − x), 0 <...
2. Let X be a continuous random variable with PDF ?fx(x)= cx(1 − x), 0 < x < 1, 0 elsewhere. (a) Find the value of c such that fX(x) is indeed a PDF. (b) Find P(−0.5 < X < 0.3). (c) Find the median of X.
A random variable Y is a function of random variable X, where y=x^2 and fx(x)=(x+1)/2 from...
A random variable Y is a function of random variable X, where y=x^2 and fx(x)=(x+1)/2 from -1 to 1 and =0 elsewhere. Determine fy(y). In this problem, there are two x values for every y value, which means x=T^-1(y)= +y^0.5 and -y^0.5. Be sure you account for both of these. Ans: fy(y)=0.5y^-0.5
Let X be a random variable. Suppose X ∼ Exp(0.5). The area under the pdf of...
Let X be a random variable. Suppose X ∼ Exp(0.5). The area under the pdf of the Exp(0.5) distribution above the interval [0, 2] is 0.6321. What is the value of the cumulative distribution function FX of X at x = 2?
The (mixed) random variable X has probability density function (pdf) fX (x) given by: fx(x)=0.5δ(x−3)+ {...
The (mixed) random variable X has probability density function (pdf) fX (x) given by: fx(x)=0.5δ(x−3)+ { c.(4-x2), 0≤x≤2 0, otherwise where c is a constant. (a) Sketch fX (x) and find the constant c. (b) Find P (X > 1). (c) Suppose that somebody tells you {X > 1} occurred. Find the conditional pdf fX|{X>1}(x), the pdf of X given that {X > 1}. (d) Find FX(x), the cumulative distribution function of X. (e) Let Y = X2 . Find...
1) The PDF of a Gaussian random variable is given by fx(x). fx(x)= (1/(3*sqrt(2pi) )*e^((x-4)^2)/18 determine...
1) The PDF of a Gaussian random variable is given by fx(x). fx(x)= (1/(3*sqrt(2pi) )*e^((x-4)^2)/18 determine a.) P(X > 4) b). P(X > 0). c). P(X < -2). 2) The joint PDF of random variables X and Y is given by fxy(x,y)=Ke^-(x+y), x>0 , y>0 Determine a. The constant k. b. The marginal PDF fX(x). c. The marginal PDF fY(y). d. The conditional PDF fX|Y(x|y). Note fX|Y(x|y) = fxy(x,y)/fY(y) e. Are X and Y independent.
Let X have the pdf fX(x) = 3(1 − x) 2 , 0 < x <...
Let X have the pdf fX(x) = 3(1 − x) 2 , 0 < x < 1. (a) Find the pdf of Y = (1 − X) 3 . Specify the distribution of Y (name and parameter values). (b) Find E(Y ) and Var(Y ).
using R :- A Gumbel random variable X has distribution function FX (x) = exp (−e^−x)....
using R :- A Gumbel random variable X has distribution function FX (x) = exp (−e^−x). a) Give a graph of FX and explain using this plot why FX is a valid cumulative probability distri- bution function. (b) Find the values of the first and third quartiles and median X and show their values on the graph. (c) Make a table of x and FX (x) for x equal to the integers from −2 to 5. (d) Find the probabilities...
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT