- 积分
- 19
- 贡献
-
- 精华
- 在线时间
- 小时
- 注册时间
- 2016-1-6
- 最后登录
- 1970-1-1
|
登录后查看更多精彩内容~
您需要 登录 才可以下载或查看,没有帐号?立即注册
x
Data<-read.csv("D:\\text.csv",sep=",",header = F)
Data<-read.csv("D:\\text.csv",header = T)
Data <-as.matrix(Data) //转换为矩阵
result1 <-gam(log(Adult) ~ s(Day))
summary(result1)
count.fields("D:\\text.csv")
attach(Data)
cor.text(Adult,Day)
result1 <- gam(log(V2) ~ s(V3))
b.plots = unique(as.character(Adult$Day))
result1 <- gam((Adult) ~ s(Day))
Data <- read.delim("D:\\Rice_insect.txt")
Data <- as.matrix(Data)
result1 <- gam(log(Adult) ~ s(Day))
summary(result1)
result2 <-gam(log(Adult) ~ s(Precipitation))//求取Adult与P的关系
summary(result2)
plot(result2,se=T,resid=T,pch=16)//绘图
result3<-gam(log(Adult)~s(Precipitation,k=9)+s(Day,k=9))
summary(result3)
//进行相关性分析的结果
cor.test(Data[,3],Data[,4],method="pearson")
Pearson's product-moment correlation
data: Data[, 2] and Data[, 3]
t = -0.3449, df = 16, p-value = 0.7347
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
-0.5314609 0.3968817
sample estimates:
cor
-0.08590609
|
|