In CIP-RIU/hidap: High Interactive Data Analysis Platform for Plant breeding

library(knitr)

traits <- params$traits
geno <- params$geno
rep <- params$rep
data <- params$data
maxp <- params$maxp

lc <- check.rcbd(traits[1], geno, rep, data)

1. Model specification and data description

There are data from r lc$nt genotypes evaluated using a randomize complete block design with r lc$nr blocks. The statistical model is $$ y_{ij} = \mu + \tau_i + \beta_j + \epsilon_{ij} $$ where

• $y_{ij}$ is the observed response with genotype $i$ and block $j$.
• $\mu$ is the mean response over all genotypes and blocks.
• $\tau_i$ is the effect for genotype $i$.
• $\beta_j$ is the effect for block $j$.
• $\epsilon_{ij}$ is the error term.

In this model we assume that the errors are independent and have a normal distribution with common variance, that is, $\epsilon_{ij} \sim N(0,\sigma_{\epsilon}^2)$.

out <- NULL
for (i in 1:length(traits))
  out <- c(out, knit_expand('child_rcbd.Rmd'))

r paste(knit(text = out), collapse = '\n')

CIP-RIU/hidap documentation built on April 30, 2021, 9:21 p.m.