Threshold Regression Without Distribution Assumption when the
... (2008), we turn the problem of an endogenous threshold variable into the problem of omitting selection correction term. Our approach is a semi-parametric method with following features. Firstly, it can consistently estimate the threshold model without any distribution assumption. Secondly, our semi- ...
... (2008), we turn the problem of an endogenous threshold variable into the problem of omitting selection correction term. Our approach is a semi-parametric method with following features. Firstly, it can consistently estimate the threshold model without any distribution assumption. Secondly, our semi- ...
Econometrics-I-20
... Our approach involved conducting a probit of alliance formation propensity, take the inverse mills and include it in the second selection equation which is also a probit of partner selection. Then, we include inverse mills from the second selection into the main model. The review team states that th ...
... Our approach involved conducting a probit of alliance formation propensity, take the inverse mills and include it in the second selection equation which is also a probit of partner selection. Then, we include inverse mills from the second selection into the main model. The review team states that th ...
An Introduction to Stan and RStan
... probability distribution associated with it. The tools of probability, in particular Bayes’ Rule, give a mathematically coherent framework for updating beliefs in the presence of data. Classical works on this point-of-view are Ramsey, Savage, Jeffreys and Jaynes [Ram31, Sav54, Jef61, Jay03].12 The p ...
... probability distribution associated with it. The tools of probability, in particular Bayes’ Rule, give a mathematically coherent framework for updating beliefs in the presence of data. Classical works on this point-of-view are Ramsey, Savage, Jeffreys and Jaynes [Ram31, Sav54, Jef61, Jay03].12 The p ...
Chapter 9 PowerPoint
... • Was Hamilton a better hitter at home than on the road? • His home PERFORMANCE was .390. • His road PERFORMANCE was .327. • A 95% confidence interval for the true difference in his ABILITY to get a hit at home and his ABILITY to get a hit on the road is -0.021 to .063. • This interval includes the ...
... • Was Hamilton a better hitter at home than on the road? • His home PERFORMANCE was .390. • His road PERFORMANCE was .327. • A 95% confidence interval for the true difference in his ABILITY to get a hit at home and his ABILITY to get a hit on the road is -0.021 to .063. • This interval includes the ...
Risk of Bayesian Inference in Misspecified Models
... function that penalizes long and mis-centered intervals. Under misspecification with ΣS = ΣM , the sandwich posterior two-sided equal-tailed intervals are a systematically better description of parameter uncertainty in the sense that they are of lower asymptotic risk under this loss function. In th ...
... function that penalizes long and mis-centered intervals. Under misspecification with ΣS = ΣM , the sandwich posterior two-sided equal-tailed intervals are a systematically better description of parameter uncertainty in the sense that they are of lower asymptotic risk under this loss function. In th ...
Document
... In the bad old days you had to work out all the sums of squares. In the good new days you can ask Excel program to do it for you. ...
... In the bad old days you had to work out all the sums of squares. In the good new days you can ask Excel program to do it for you. ...
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.