# NOT RUN {
data(DataExam5.2)
library(tidyverse)
library(ggplot2)
fm5.7 <- aov(formula = height~env*gen
,data = DataExam5.2
#, subset
#, weights
#, na.action
, method = "qr"
, model = TRUE
, x = FALSE
, y = FALSE
, qr = TRUE
, singular.ok = TRUE
, contrasts = NULL
)
anova(fm5.7)
fm5.9 <- aov(formula = height~env*gen
,data = DataExam5.2
#, subset
#, weights
#, na.action
, method = "qr"
, model = TRUE
, x = FALSE
, y = FALSE
, qr = TRUE
, singular.ok = TRUE
, contrasts = NULL
)
anova(fm5.9)
b<-anova(fm5.9)
Res <- length(b[["Sum Sq"]])
df <- 384
MSS <- 964
b[["Df"]][Res] <- df
b[["Sum Sq"]][Res] <- MSS*df
b[["Mean Sq"]][Res] <- b[["Sum Sq"]][Res]/b[["Df"]][Res]
b[["F value"]][1:Res-1] <- b[["Mean Sq"]][1:Res-1]/b[["Mean Sq"]][Res]
b[["Pr(>F)"]][Res-1] <- df(b[["F value"]][Res-1],b[["Df"]][Res-1],b[["Df"]][Res])
b
X1<- DataExam5.2 %>%
group_by(env) %>%
summarize(SiteMean=mean(height))
Data5.2new<-merge(DataExam5.2,X1, by.x="env",by.y="env")
RegCoeff <- function(Data5.2new)
{
fm <- lm(formula = height ~ SiteMean
,data = Data5.2new)
setNames(data.frame(t(coef(fm)))
,c("intercept", "slope"))
}
RegCoeff1 <- Data5.2new %>%
group_by(gen) %>%
do(RegCoeff(.))
SeedLot.Mean <- DataExam5.2 %>%
group_by(gen) %>%
summarize(mean(height))
Tab5.14 <- data.frame(RegCoeff1,Mean=SeedLot.Mean$'mean(height)')
Tab5.14
ggplot(Tab5.14,aes(x=Mean,y=slope))+
geom_point(size=2)+
theme_bw()+
geom_text(aes(label=gen),hjust=0, vjust=0)+
labs(x="Seed Lot Mean",y="Regression Coefficient")
Code<-c("a","a","a","a","b","b","b","b","c","d","d","d","d","e","f","g",
"h","h","i","i","j","k","l","m","n","n","n","o","p","p","q","r",
"s","t","t","u","v")
Tab5.14$Code<-Code
ggplot(Tab5.14,aes(x=Mean,y=slope))+
geom_point(size=2)+
theme_bw()+
geom_text(aes(label=Code),hjust=-0.5, vjust=-0.5)+
labs(x="Seed Lot Mean",y="Regression Coefficient")
# }
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