library(knitr) traits <- params$traits geno <- params$geno data <- params$data maxp <- params$maxp
There are data from r nlevels(as.factor(data[, geno]))
genotypes, evaluated using a completely randomized design. The statistical model is
$$
y_{ij} = \mu + \tau_i + \epsilon_{ij}
$$
where
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_crd.Rmd'))
r paste(knit(text = out), collapse = '\n')
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