calculate_weights: Provided a point, a data frame, and lambda, this function...
In ddsjoberg/sjosmooth: Kernel smoothing for time to event data
Description
Provided a point, a data frame, and lambda, this function calculates the
weights each observation in the data frame provides the calculations
Usage
1
calculate_weights(dist, lambda, kernel, weighting_var)
Arguments
dist
distance vector
lambda
The radius of the kernel for tri-cubic, Epanechnikov, and flat kernels.
The standard deviation for the Gaussian kernel.
kernel
type of kernel to use for weight calculation
ddsjoberg/sjosmooth documentation built on May 14, 2019, 5:16 p.m.
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Description
Provided a point, a data frame, and lambda, this function calculates the weights each observation in the data frame provides the calculations
Usage
1 | calculate_weights(dist, lambda, kernel, weighting_var)
|
Arguments
dist |
distance vector |
lambda |
The radius of the kernel for tri-cubic, Epanechnikov, and flat kernels. The standard deviation for the Gaussian kernel. |
kernel |
type of kernel to use for weight calculation |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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