英文:
Calculate linear regression slope with moving window
问题
我需要计算每5行数据的斜率，然后跳过1行数据，再计算下5行数据的斜率，如此循环。如果数据集的末尾不足5行数据，则将斜率设置为NA或不计算。
mtcars[c(1:5),c(1,3)] %>%
mutate(slope = lm(c(mpg) ~ c(disp))$coefficients[[2]])
我需要计算接下来5行数据的斜率，间隔为1行：
mtcars[c(2:6),c(1,3)] %>%
mutate(slope = lm(c(mpg) ~ c(disp))$coefficients[[2]])
英文:
I have a dataframe and i need to automate the slope calculation by lm each 5 rows and jump 1 point and calculate slope with next 5 points and again jump 1 point and calculate slope with 5 points. And if the end of datafra when you not have 5 points put NA or no calculate slope
mtcars[c(1:5),c(1,3)] %>%
mutate(slope = lm(c(mpg) ~ c(disp))$coefficients[[2]])
I need to calculate slope to next 5 points with gap = 1
mtcars[c(2:6),c(1,3)] %>%
mutate(slope = lm(c(mpg) ~ c(disp))$coefficients[[2]])
答案1
得分: 0
使用map来迭代每一行的行号：
# 玩具数据集
data <- tibble(
x = 1:50,
y = rnorm(50))
data %>%
# 对于每一行，获取独立变量的系数（即x的系数）
mutate(model = c(map(1:(nrow(data) - 4), ~lm(y ~ x, data = data[.x:(.x + 4), ])$coefficients[2]), NA, NA, NA, NA) %>% unlist())
# 一个tibble：50 × 3
x y model
<int> <dbl> <dbl>
1 1 -2.52 0.775
2 2 -0.455 0.370
3 3 -0.914 0.333
4 4 -1.14 0.221
5 5 1.70 -0.214
6 6 0.0893 0.0863
7 7 0.138 -0.305
8 8 0.748 -0.329
9 9 0.298 -0.239
10 10 0.441 0.274
# ℹ 还有40行
英文:
Using map to iterate over each row number:
# toy dataset
data <- tibble(
x = 1:50,
y = rnorm(50))
data %>%
# for each row, get the coefficient of the independent variable (i.e the coefficient of x)
mutate(model = c(map(1:(nrow(data) - 4), ~lm(y ~ x, data = data[.x:(.x + 4), ])$coefficients[2]), NA, NA, NA, NA) %>% unlist())
# A tibble: 50 × 3
x y model
<int> <dbl> <dbl>
1 1 -2.52 0.775
2 2 -0.455 0.370
3 3 -0.914 0.333
4 4 -1.14 0.221
5 5 1.70 -0.214
6 6 0.0893 0.0863
7 7 0.138 -0.305
8 8 0.748 -0.329
9 9 0.298 -0.239
10 10 0.441 0.274
# ℹ 40 more rows
答案2
得分: 0
rollapply会在指定大小（5）的滑动窗口上计算任意函数。我们定义斜率如所示，或者可以选择使用被注释掉的定义，它等效但速度较慢。
下面的代码提供了一个居中对齐的窗口，因此两端各有2行NA值，但rollapplyr在末尾加上r可以用于指定右对齐的窗口，在这种情况下，它们都将位于开头。如果需要，rollapply的align="left"参数可用于指定左对齐。
library(dplyr)
library(zoo)
# slope <- function(x) coef(lm(x[, 2] ~ x[, 1]))[[2]]
slope <- function(x) cov(x[, 1], x[, 2]) / var(x[, 1])
mtcars %>%
mutate(slope = rollapply(cbind(disp, mpg), 5, slope, by.column=FALSE, fill=NA))
英文:
rollapply will compute an arbitrary function on a moving window of indicated szie (5). We define slope as shown or optionally use the commented out definition which is equivalent but slower.
The code below gives a center aligned window so there are 2 NA rows on either end but rollapplyr with an r on the end can be used to specify a right aligned window in which case they will all be at the beginning. The align="left" argument of rollapply can be used to specify left alignment if that is wanted.
library(dplyr)
library(zoo)
# slope <- function(x) coef(lm(x[, 2] ~ x[, 1]))[[2]]
slope <- function(x) cov(x[, 1], x[, 2]) / var(x[, 1])
mtcars %>%
mutate(slope = rollapply(cbind(disp, mpg), 5, slope, by.column=FALSE, fill=NA))
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