Let be a sample (size n = 1) from the exponential distribution, which has the pdf where is an unknown parameter. Let's define a statistic as . Is a sufficient statistic for ?
Let be a sample (size n = 1) from the exponential distribution, which has the pdf...
Let be a sample (size n=1) from the exponential distribution, which has the pdf , where is an unknown parameter. Let's define a statistic as . Is a sufficient statistic for ? We were unable to transcribe this imagef(x: λ) = Xe We were unable to transcribe this imageT(X) = 1122 T(X) We were unable to transcribe this image
0Let X1, ....., Xn be iid Random variable from a Uniform distribution with pdf given by . (1) Is the 2-dimensional statistics T1(X) = (X(1), X(n)) a complete sufficient statistics? Justify your answer (2) Is the one-dimensional statistic a complete sufficient statistic? Justify your answer We were unable to transcribe this imageWe were unable to transcribe this imageWe were unable to transcribe this image
are order statistics from same distribution . Sample size is 3. Define and Finding marginal density of . We were unable to transcribe this imageplz) = 1 We were unable to transcribe this imageWe were unable to transcribe this imageWe were unable to transcribe this imageWe were unable to transcribe this image
are order statistics from same distribution . Sample size is 3. Define and Finding joint density of and . We were unable to transcribe this imageplz) = 1 We were unable to transcribe this imageWe were unable to transcribe this imageWe were unable to transcribe this imageWe were unable to transcribe this imageWe were unable to transcribe this image
For , let be the order statistics of independent draws from . (1) Find the PDF of . (2) Compute . We were unable to transcribe this imageWe were unable to transcribe this image(2n+1 Unif -1,1 We were unable to transcribe this imageWe were unable to transcribe this image
Suppose is a random sample from , where and . (a) Find a minimal sufficient statistic for . (b) Find a complete statistic for . (c) Show that is independent of , where . 7l We were unable to transcribe this imageWe were unable to transcribe this imageWe were unable to transcribe this imageWe were unable to transcribe this imageWe were unable to transcribe this imageに! Х-Л. We were unable to transcribe this image
STATISTICS. REGIONS OF CONFIDENCE Let be a simple random sample (n) of the density , Find the confidence interval of 95% for the variance of the population. Thank you for your explanations. We were unable to transcribe this imageWe were unable to transcribe this imageWe were unable to transcribe this image
Doob’s Decomposition: Let be a submartingale relative to the filtration . Show that there is a martingale and a predictable sequence such that for all and . (Xm)m>o We were unable to transcribe this image(Mm)m>o (Am)m20 We were unable to transcribe this imagem>0 We were unable to transcribe this image
#4. Let , , and be a random sample from f. Find the UMVUE for We were unable to transcribe this imageWe were unable to transcribe this imageWe were unable to transcribe this imageWe were unable to transcribe this imageWe were unable to transcribe this image
Let and be two Gaussian random variables. (1) Sketch the PDFs of , on the same chart. (2) Assuming , are independent, compute . X1N(4.2,1) X2~ N(12,70 We were unable to transcribe this imageWe were unable to transcribe this imageWe were unable to transcribe this imageWe were unable to transcribe this imageWe were unable to transcribe this image