Hi
One method is from DMwR package (
https://cran.r-project.org/web/packages/DMwR/DMwR.pdf) :
knnImputation
Fill in NA values with the values of the nearest neighbours
Description
Function that fills in all NA values using the k Nearest Neighbours of
each case with NA values.
By default it uses the values of the neighbours and obtains an weighted
(by the distance to the case)
average of their values to fill in the unknows. If meth=?median? it uses
the median/most frequent
value, instead.
Usage
knnImputation(data, k = 10, scale = T, meth = "weighAvg", distData = NULL)
Yours sincerely / Med venlig hilsen
Frede Aakmann T?gersen
Specialist, M.Sc., Ph.D.
Plant Performance & Modeling
Technology & Service Solutions
T +45 9730 5135
M +45 2547 6050
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*From:* R-sig-Geo [mailto:r-sig-geo-bounces at r-project.org] *On Behalf Of *Metastate
Metastate
*Sent:* 25. august 2015 05:05
*To:* r-sig-geo at r-project.org
*Subject:* [R-sig-Geo] Impute missing value using k nearest neighbour
Hi,
I have a data set with location ID (FIPS), latitude and longitude of the
location, V1 to v3 that are some features for relevant location. The
dataset have more than 3000 locations. Please see the attached file for a
small sample. In the sample file, you can see there are some missing values
for V2 and V3 at FIPS of 26089. Does anyone know any r package that can
impute the missing values based on k nearest neighbor using the distance
matrix calculated from latitude and longitude?
Really appreciation for your kindly help or suggestion.
Meta