# gomez.seedrate: Rice yield at six different densities In agridat: Agricultural Datasets

## Description

Rice yield at six different densities

## Format

A data frame with 24 observations on the following 3 variables.

`rate`

kg seeds per hectare

`rep`

rep (block), four levels

`yield`

yield, kg/ha

## Details

Rice yield at six different densities in an RCB design.

## Source

Gomez, K.A. and Gomez, A.A. 1984, Statistical Procedures for Agricultural Research. Wiley-Interscience. Page 26.

Used with permission of Kwanchai Gomez.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20``` ```data(gomez.seedrate) dat <- gomez.seedrate require(lattice) xyplot(yield ~ rate, data=dat, group=rep, type='b', main="gomez.seedrate", auto.key=list(columns=4)) # Quadratic response. Use raw polynomials so we can compute optimum m1 <- lm(yield ~ rep + poly(rate,2,raw=TRUE), dat) -coef(m1)/(2*coef(m1)) # Optimum is at 29 # Plot the model predictions if(require(latticeExtra)){ newdat <- expand.grid(rep=levels(dat\$rep), rate=seq(25,150)) newdat\$pred <- predict(m1, newdat) p1 <- aggregate(pred ~ rate, newdat, mean) # average reps xyplot(yield ~ rate, data=dat, group=rep, type='b', main="gomez.seedrate (with model predictions)", auto.key=list(columns=4)) + xyplot(pred ~ rate, p1, type='l', col='black', lwd=2) } ```

agridat documentation built on May 2, 2019, 4:01 p.m.