na.interpolation

From imputeTS v2.7 by Steffen Moritz

Missing Value Imputation by Interpolation

Uses either linear, spline or stineman interpolation to replace missing values.

Usage

na.interpolation(x, option = "linear", ...)

Arguments

x

Numeric Vector (vector) or Time Series (ts) object in which missing values shall be replaced

option

Algorithm to be used. Accepts the following input:

"linear" - for linear interpolation using approx
"spline" - for spline interpolation using spline
"stine" - for Stineman interpolation using stinterp

...

Additional parameters to be passed through to approx or spline interpolation functions

Details

Missing values get replaced by values of a approx, spline or stinterp interpolation.

Value

Vector (vector) or Time Series (ts) object (dependent on given input at parameter x)

References

Johannesson, Tomas, et al. (2015). "Package stinepack".

Examples

# NOT RUN {
#Prerequisite: Create Time series with missing values
x <- ts(c(2,3,4,5,6,NA,7,8))

#Example 1: Perform linear interpolation
na.interpolation(x)

#Example 2: Perform spline interpolation
na.interpolation(x, option = "spline")

#Example 3: Perform stine interpolation
na.interpolation(x, option = "stine")

#Example 4: Same as example 1, just written with pipe operator
x %>% na.interpolation

#Example 5: Same as example 2, just written with pipe operator
x %>% na.interpolation(option = "spline")

# }

Documentation reproduced from package imputeTS, version 2.7, License: GPL-3

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