The observation on the time series variable Y made at date tis denoted as Y, and the total number of observations is denoted as T. Suppose Y represents GDP of a country. A researcher has the past 10 years of GDP data, from 2009 to 2019. Ytj is the GDP for the year t-j (j=t., T, and t=0, 1, 2,., 10) and Y, is the GDP for the current year. The researcher wants to estimate the first four autocorrelations, P, =1,.., 4), using this data. Suppose Var(Y,) = 19.16. Also assume that the first four autocovariance estimates are as follows: j=1 j=2 j=3 j=4 15.98 13.69 | 12.76 11.14
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
Trending now
This is a popular solution!
Step by step
Solved in 3 steps with 18 images
