Kernel Regression Mastery Quiz

A visually engaging illustration of kernel regression concepts, featuring graphs, data points, and rings representing kernel fun<wbr>ctions in a colorful, informative style.

Kernel Regression Mastery Quiz

Test your knowledge of kernel regression and nonparametric methods with this engaging quiz. Dive deep into concepts like bias, variance, and bandwidth selection rules, designed for learners ranging from beginners to experts in the field.

In this quiz, you will:

  • Assess your understanding of kernel estimators.
  • Explore various bandwidth selection methods.
  • Consolidate your knowledge about kernel density functions.
12 Questions3 MinutesCreated by AnalyzingData42
A Nonparametric regression is a model with...?
No parameter
A few parameters
Several parameters
Many parameters
Kernel regression is the...nonparametric regression
Simplest
Best
Most general
Most complex
Kernel regression is an extension of..
Nonlinear regr.
Polynomial regr
Moving average
Dummy variables
Which of the following densities is not a 2nd order kernel?
That for N (0,1)
That for t(6)
That for uniform on [0, 1]
That for t(8)
The value c in the kernel K(u)=c(1-|u|) on [-1, 1] is
1
2
3
4
The global optimal bandwidth of a kernel regr. minimizes
The bias B(h)
The variance V(h)
The MSE(x)
The MISE on [c,d]
The bias of a kernel estimator in the interior is of the order
O(h^-2)
O(h²)
O[(nh)^-1]
O(nh)
The variance of a kernel estimator is of the order
O(h^-2)
O(h²)
O[(nh)^-1]
O(nh)
The local optimal h of a kernel estimator in the interior is of
O(n^-1/10)
O(n^-2/10)
O(n^-3/10)
O(n^-4/10)
Which of the following appr. Is not a bandwidth selection rule?
The plug-in
The kernel smoothing
The double-smoothing
Cross-validation
Let B²(h) & V(h) be the sq. Bias resp. The variance. The larger h
The smaller B²(h)
The smaller V(h)
The smaller the MSE
The larger the MSE
The cross-validation bandwidth selection rule is
The best
The simplest
The quickest
Valueless
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