Serial Correlation and Heteroskedasticity in Time Series Regressions
... Because the Gauss-Markov Theorem requires both homoskedasticity and serially uncorrelated errors, OLS is no longer BLUE in the presence of serial correlation. Even more importantly, the usual OLS standard errors and test statistics are not valid, even asymptotically. Consider an AR(1) serial correla ...
... Because the Gauss-Markov Theorem requires both homoskedasticity and serially uncorrelated errors, OLS is no longer BLUE in the presence of serial correlation. Even more importantly, the usual OLS standard errors and test statistics are not valid, even asymptotically. Consider an AR(1) serial correla ...
MCF 3MI - U4 - 00 - All Lessons
... Use your equation to find the height of the ball after 2.25 seconds. ...
... Use your equation to find the height of the ball after 2.25 seconds. ...
A Note on Standard Deviation and RMS
... THE AUSTRALIAN SURVEYOR Vol. 44 No. 1 A probability density function is a non-negative function where the area under the curve is one. For f ( x ) ³ 0 and ...
... THE AUSTRALIAN SURVEYOR Vol. 44 No. 1 A probability density function is a non-negative function where the area under the curve is one. For f ( x ) ³ 0 and ...
German tank problem
In the statistical theory of estimation, the problem of estimating the maximum of a discrete uniform distribution from sampling without replacement is known in English as the German tank problem, due to its application in World War II to the estimation of the number of German tanks.The analyses illustrate the difference between frequentist inference and Bayesian inference.Estimating the population maximum based on a single sample yields divergent results, while the estimation based on multiple samples is an instructive practical estimation question whose answer is simple but not obvious.