数据:
Y X levels
y1 x1 2
...
lm(Y~X,I(levels==1))
I(levels==1)
是否在levels==1
下?如果没有,只有在Y
等于X
时才能对levels
与1
进行回归?
答案 0 :(得分:2)
从nlme包中查看lmList
set.seed(12345)
dataset <- data.frame(x = rnorm(100), y = rnorm(100), levels = gl(2, 50))
dataset$y <- with(dataset,
y + (0.1 + as.numeric(levels)) * x + 5 * as.numeric(levels)
)
library(nlme)
models <- lmList(y ~ x|levels, data = dataset)
输出是lm模型的列表,每个级别一个
models
Call:
Model: y ~ x | levels
Data: dataset
Coefficients:
(Intercept) x
1 4.964104 1.227478
2 10.085231 2.158683
Degrees of freedom: 100 total; 96 residual
Residual standard error: 1.019202
这是第一个模型的摘要
summary(models[[1]])
Call:
lm(formula = form, data = dat, na.action = na.action)
Residuals:
Min 1Q Median 3Q Max
-2.16569 -1.04457 -0.00318 0.78667 2.65927
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.9641 0.1617 30.703 < 2e-16 ***
x 1.2275 0.1469 8.354 6.47e-11 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 1.128 on 48 degrees of freedom
Multiple R-squared: 0.5925, Adjusted R-squared: 0.584
F-statistic: 69.78 on 1 and 48 DF, p-value: 6.469e-11
答案 1 :(得分:1)
您拥有subset
的参数lm
,这是一个示例。
x <- rnorm(100)
y <- rnorm(100, sd=0.1)
y[1:50] <- y[1:50] + 3*x[1:50] + 10 # line y = 3x+10
y[51:100] <- y[51:100] + 8*x[51:100] - 5 # line y = 8x-5
levels <- rep(1:2, each=50, len=100)
data = data.frame(x=x, y=y, levels=levels)
lm(y ~ x, data=data, subset=levels==1) # regression for the first part
Coefficients: (Intercept) x
10.015 2.996
lm(y ~ x, data=data, subset=levels==2) # second part
Coefficients: (Intercept) x
-4.986 8.000
您将I(levels==1)
隐式传递给subset
内的lm
。
答案 2 :(得分:0)
我不确定。但是这段代码似乎表明你是对的。
my.data <- "x y level
1 2 1
2 4 2
3 4 1
4 3 2
5 5 1
6 5 2
7 7 1
8 6 2
9 10 1
10 5 2"
my.data2 <- read.table(textConnection(my.data), header = T)
my.data2
lm(x ~ y,I(level==1), data=my.data2)
my.data <- "x y level
1 2 1
3 4 1
5 5 1
7 7 1
9 10 1"
my.data2 <- read.table(textConnection(my.data), header = T)
my.data2
lm(x ~ y, data=my.data2)