Exam5.1 {eda4treeR} | R Documentation |
Exam5.1 presents the height of 27 seedlots from 4 sites.
Muhammad Yaseen (myaseen208@gmail.com)
Sami Ullah (samiullahuos@gmail.com)
Williams, E.R., Matheson, A.C. and Harwood, C.E. (2002).Experimental Design and Analysis for Tree Improvement. CSIRO Publishing.
data(DataExam5.1)
library(tidyverse)
library(ggplot2)
fm5.4 <- lm(formula = Ht~Site*SeedLot
,data = DataExam5.1
#, subset
#, weights
#, na.action
, method = "qr"
, model = TRUE
, x = FALSE
, y = FALSE
, qr = TRUE
, singular.ok = TRUE
, contrasts = NULL
)
anova(fm5.4)
DataExam5.1 %>%
dplyr::group_by(Site) %>%
dplyr::summarize(Mean=mean(Ht))
DataExam5.1 %>%
dplyr::group_by(SeedLot) %>%
dplyr::summarize(Mean=mean(Ht))
b<-anova(fm5.4)
Res <- length(b[["Sum Sq"]])
df <- 208
MSS <- 1040
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
RegCoeff <- function(DataExam5.1)
{
fm <- lm(formula = Ht ~ SiteMean
,data = DataExam5.1)
setNames(data.frame(t(coef(fm)))
,c("intercept", "slope"))
}
X1 <- DataExam5.1%>%group_by(Site)%>%summarize(sitemean=mean(Ht))
X2 <- filter(DataExam5.1, SeedLot=="13653")
X3 <- filter(DataExam5.1, SeedLot=="13871")
dffig5.1 <-merge(rbind(X2,X3),X1)
ggplot(dffig5.1, aes(x=sitemean, y=Ht, color=SeedLot, shape=SeedLot)) +
geom_point() +
geom_smooth(method=lm, se=FALSE, fullrange=TRUE)+
theme_classic()+
labs(y="Seedlot mean",x="Sitemean")
RegCoeff <- DataExam5.1 %>%
group_by(SeedLot) %>%
do(RegCoeff(.))
SeedLot.Mean <- DataExam5.1 %>%
group_by(SeedLot) %>%
summarize(mean(Ht))
Tab5.10 <- data.frame(RegCoeff,Mean=SeedLot.Mean$'mean(Ht)')
Tab5.10
ggplot(Tab5.10,aes(x=Mean,y=slope))+
geom_point(size=2)+
theme_bw()+
labs(x="Seed Lot Mean",y="Regression Coefficient")