Hayman {DiallelAnalysisR}

Diallel Analysis using Hayman Approach

Description

Hayman is used for performing Diallel Analysis using Hayman's Approach.

Usage

Hayman(y, Rep, Cross1, Cross2, data)

Arguments

y

Numeric Response Vector

Rep

Replicate as factor

Cross1

Cross 1 as factor

Cross2

Cross 2 as factor

data

A data.frame

Details

Diallel Analysis using Haymans's approach.

Value

Means Means

ANOVA Analysis of Variance (ANOVA) table

Genetic.Components Genetic Components

Effects Effects of Crosses

StdErr Standard Errors of Crosses

Author(s)

Muhammad Yaseen ([e-mail])

References

1. Hayman, B. I. (1954 a) The Theory and Analysis of Diallel Crosses. Genetics, 39, 789–809.

2. Hayman, B. I. (1954 b) The Analysis of Variance of Diallel Tables. Biometrics, 10, 235–244.

3. Hayman, B. I. (1957) Interaction, Heterosis and Diallel Crosses. Genetics, 42, 336–355.

4. Singh, R. K. and Chaudhary, B. D. (2004) Biometrical Methods in Quantitative Genetic Analysis. New Delhi: Kalyani.

See Also

Griffing , HaymanData

Examples

#------------------------------------------
## Diallel Analysis with Haymans's Aproach
#------------------------------------------

Hayman1Data <-
 Hayman(
     y      = Yield
   , Rep    = Rep
   , Cross1 = Cross1
   , Cross2 = Cross2
   , data   = HaymanData
   )

Hayman1Data
names(Hayman1Data)

Hayman1DataMeans <- Hayman1Data$Means
Hayman1DataANOVA <- Hayman1Data$ANOVA
Hayman1DataWr.Vr.Table <- Hayman1Data$Wr.Vr.Table

Hayman1DataComponents.of.Variation <- Hayman1Data$Components.of.Variation
Hayman1DataOther.Parameters <- Hayman1Data$Other.Parameters
Hayman1DataFr <- Hayman1Data$Fr

#----------------
# Wr-Vr Graph
#----------------
VOLO     <- Hayman1Data$VOLO
In.Value <- Hayman1Data$In.Value
a        <- Hayman1Data$a
b        <- Hayman1Data$b
Wr.Vr    <- Hayman1Data$Wr.Vr.Table


library(ggplot2)
ggplot(data=data.frame(x=c(0, max(In.Value, Wr.Vr$Vr, Wr.Vr$Wr, Wr.Vr$Wrei))), aes(x)) +
  stat_function(fun=function(x) {sqrt(x*VOLO)}, color="blue") +
  geom_hline(yintercept = 0) +
  geom_vline(xintercept = 0) +
  geom_abline(intercept = a, slope = b) +
  geom_abline(intercept = mean(Wr.Vr$Wr)-mean(Wr.Vr$Vr), slope = 1) +
  geom_segment(aes(
      x     = mean(Wr.Vr$Vr)
    , y     = min(0, mean(Wr.Vr$Wr))
    , xend  = mean(Wr.Vr$Vr)
    , yend  = max(0, mean(Wr.Vr$Wr))
  )
  , color = "green"
  ) +
  geom_segment(aes(
      x     = min(0, mean(Wr.Vr$Vr))
    , y     = mean(Wr.Vr$Wr)
    , xend  = max(0, mean(Wr.Vr$Vr))
    , yend  = mean(Wr.Vr$Wr)
  )
  , color = "green"
  )  +
  lims(x=c(min(0, Wr.Vr$Vr, Wr.Vr$Wrei), max(Wr.Vr$Vr, Wr.Vr$Wrei)),
       y=c(min(0, Wr.Vr$Wr, Wr.Vr$Wrei), max(Wr.Vr$Wr, Wr.Vr$Wri))
  ) +
  labs(
         x = expression(V[r])
       , y = expression(W[r])
       , title = expression(paste(W[r]-V[r] , " Graph"))
       ) +
  theme_bw()