besag.bayesian {agridat} R Documentation

## RCB experiment of spring barley in United Kingdom

### Description

RCB experiment of spring barley in United Kingdom

### Format

A data frame with 225 observations on the following 4 variables.

`col`

column (also blocking factor)

`row`

row

`yield`

yield

`gen`

variety/genotype

### Details

RCB design, each column is one rep.

Used with permission of David Higdon.

### Source

Besag, J. E., Green, P. J., Higdon, D. and Mengersen, K. (1995). Bayesian computation and stochastic systems. Statistical Science, 10, 3-66. https://www.jstor.org/stable/2246224

### References

Davison, A. C. 2003. Statistical Models. Cambridge University Press. Pages 534-535.

### Examples

```## Not run:

library(agridat)
data(besag.bayesian)
dat <- besag.bayesian

# Yield values were scaled to unit variance
# var(dat\$yield, na.rm=TRUE)
# .999

# Besag Fig 2. Reverse row numbers to match Besag, Davison
dat\$rrow <- 76 - dat\$row
libs(lattice)
xyplot(yield ~ rrow|col, dat, layout=c(1,3), type='s',
xlab="row", ylab="yield", main="besag.bayesian")

libs(asreml)

# Use asreml to fit a model with AR1 gradient in rows
dat <- transform(dat, cf=factor(col), rf=factor(rrow))
m1 <- asreml(yield ~ -1 + gen, data=dat, random= ~ ar1v(rf))
m1 <- update(m1)
m1 <- update(m1)
m1 <- update(m1)

# Visualize trends, similar to Besag figure 2.
# Need 'as.vector' because asreml4 uses a named vector
dat\$res <- unname(m1\$resid)
dat\$geneff <- coef(m1)\$fixed[as.numeric(dat\$gen)]
dat <- transform(dat, fert=yield-geneff-res)
libs(lattice)
xyplot(geneff ~ rrow|col, dat, layout=c(1,3), type='s',
main="besag.bayesian - Variety effects", ylim=c(5,15 ))
xyplot(fert ~ rrow|col, dat, layout=c(1,3), type='s',
main="besag.bayesian - Fertility", ylim=c(-2,2))
xyplot(res ~ rrow|col, dat, layout=c(1,3), type='s',
main="besag.bayesian - Residuals", ylim=c(-4,4))

## End(Not run)
```

[Package agridat version 1.18 Index]