chapter10
... Calculating the Linear Correlation Coefficient We’ll only calculate r using technology, and we’ll see how to do that later on in this section. Round r to 3 decimal places The coefficient of determination, r2 (the square of the linear correlation coefficient): r2 Is the proportion of explained varia ...
... Calculating the Linear Correlation Coefficient We’ll only calculate r using technology, and we’ll see how to do that later on in this section. Round r to 3 decimal places The coefficient of determination, r2 (the square of the linear correlation coefficient): r2 Is the proportion of explained varia ...
Predictable Changes in Yields and Forward Rates*
... hypothesis, these studies nevertheless provide useful summaries of interest rate dynamics. They illustrate, for example, how future interest rates can be predicted with (say) spreads between long and short rates. The modern \arbitrage-free" theory of bond pricing continues to develop along lines lai ...
... hypothesis, these studies nevertheless provide useful summaries of interest rate dynamics. They illustrate, for example, how future interest rates can be predicted with (say) spreads between long and short rates. The modern \arbitrage-free" theory of bond pricing continues to develop along lines lai ...
Sure Independence Screening for Ultra
... is an n-vector of i.i.d. random errors. When dimension p is high, it is often assumed that only a small number of predictors among X1 , · · · , Xp contribute to the response, which amounts to assuming ideally that the parameter vector β is sparse. With sparsity, variable selection can improve estima ...
... is an n-vector of i.i.d. random errors. When dimension p is high, it is often assumed that only a small number of predictors among X1 , · · · , Xp contribute to the response, which amounts to assuming ideally that the parameter vector β is sparse. With sparsity, variable selection can improve estima ...
Shrinkage Tuning Parameter Selection with a Diverging Number of
... Contemporary research frequently deals with problems involving a diverging number of parameters (Fan and Li, 2006). For the sake of variable selection, various shrinkage methods have been developed. Those methods include but are not limited to: least absolute shrinkage and selection operator (Tibshi ...
... Contemporary research frequently deals with problems involving a diverging number of parameters (Fan and Li, 2006). For the sake of variable selection, various shrinkage methods have been developed. Those methods include but are not limited to: least absolute shrinkage and selection operator (Tibshi ...
![[2008] A weakly informative default prior distribution for logistic and](http://s1.studyres.com/store/data/006646246_1-37662a9b36bde534a308d4a59b11f76d-300x300.png)
[2008] A weakly informative default prior distribution for logistic and
... a somewhat informative prior distribution that can nonetheless be used in a wide range of applications. As always with default models, our prior can be viewed as a starting point or placeholder—a baseline on top of which the user can add real prior information as necessary. For this purpose, we want ...
... a somewhat informative prior distribution that can nonetheless be used in a wide range of applications. As always with default models, our prior can be viewed as a starting point or placeholder—a baseline on top of which the user can add real prior information as necessary. For this purpose, we want ...
