bickde
(Package: ICE) :
Bandwidth choice for Interval-Censored Kernel Density Estimation
Likelihood Cross-Validation bandwidth choice for interval-censored kernel density estimates. Also computed is the direct-plug-in estimate (using the KernSmooth function dpik based on the interval midpoints.
● Data Source:
CranContrib
● Keywords: models
● Alias: bickde
●
0 images
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icllde
(Package: ICE) :
Interval-Censored Local Linear Density Estimation
This is the local linear version of ickde.
● Data Source:
CranContrib
● Keywords: models
● Alias: icllde
●
1 images
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iclocpoly
(Package: ICE) :
Interval-Censored Local Polynomial Regression Estimation
Local polynomial regression estimation for interval-censored data.
● Data Source:
CranContrib
● Keywords: models
● Alias: iclocpoly
●
1 images
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inmost
(Package: ICE) :
Innermost Intervals for Interval-Censored Data
This function calculates the innermost intervals (Turnbull's algorithm) for interval-censored data. Right-censored data is not allowed at this point.
● Data Source:
CranContrib
● Keywords: models
● Alias: inmost
●
0 images
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likelihoodcv
(Package: ICE) :
Log Cross-Validated Likelihood
Log Cross-Validated Likelihood for interval-censored data. The likelihood is the product of integrals over the innermost intervals. Leave-one-out cross-validation here is accomplished by leaving out each innermost interval and re-computing the integral using the remaining data.
● Data Source:
CranContrib
● Keywords: models
● Alias: likelihoodcv
●
0 images
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ickde
(Package: ICE) :
Interval-Censored Kernel Density Estimation
Iterated conditional expectation kernel density estimation using a local constant. The bandwidth is assumed fixed. (See the example for a way to get a quick ballpark estimate of the bandwidth.) The gaussian, epanechnikov and biweight kernels can be used. Note that the bandwidth estimate would have to be adjusted before using with epanechnikov or biweight.
● Data Source:
CranContrib
● Keywords: models
● Alias: ickde
●
1 images
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