数据线性插值 [英] Linear interpolation of data

问题描述

我有一个带有年份(x)和相关百分比(y)的数据框

I have a data frame with the year (x) and an associated percentage (y)

data.frame(x = c(1997,2000,2003,2006,2009,2010,2013,2014),
           y = c(.02,.023,.025,.024,.026,.027,.029,.031)

这是此数据框的折线图:

Here is a line chart of this data frame :

我想对数据进行插值，以基于线性回归获得缺失年份的百分比.

I would like to interpolate my data to get the percentage of missing years based on a linear regression.

我可以为每条曲线建立线性模型，但这会很乏味.

I could make a linear model of each piece of curve but it would be tedious.

有没有一种简单的方法可以用R做到这一点?

Is there a simple way to do it with R?

输入:

df = data.frame(
  year=c(1997,2000,2003,2006,2009,2010,2013,2014),
  percent=c(0.020, 0.023, 0.025, 0.024, 0.026, 0.027, 0.029, 0.031)
)

输出(对于功能f):

f(2006)==0.024
f(2007)==0.024.666
f(2008)==0.025.333
f(2009)==0.026

推荐答案

一种方法是对 zoo 使用线性 inter 定位:

One way is to use linear inter polation with zoo:

library(tidyr)
library(zoo)

df_complete <- complete(df, year = full_seq(year, 1))
df_complete$percent <- na.approx(df_complete$percent)


plot(df_complete)

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