# streibig.competition: Competition experiment between barley and sinapis. In agridat: Agricultural Datasets

## Description

Competition experiment between barley and sinapis, at different planting rates.

## Format

A data frame with 135 observations on the following 8 variables.

`pot`

pot number

`bseeds`

barley seeds sown

`sseeds`

sinapis seeds sown

`block`

block

`bfwt`

barley fresh weight

`sfwt`

sinapis fresh weight

`bdwt`

barley dry weight

`sdwt`

sinapis dry weight

## Details

The source data (in McCullagh) also contains a count of plants harvested (not included here) that sometimes is greater than the number of seeds planted.

Used with permission of Jens Streibig.

## Source

Peter McCullagh, John A. Nelder. Generalized Linear Models, page 318-320.

## References

Oliver Schabenberger and Francis J Pierce. 2002. Contemporary Statistical Models for the Plant and Soil Sciences. CRC Press. Page 370-375.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33``` ```## Not run: library(agridat) data(streibig.competition) dat <- streibig.competition # See Schaberger and Pierce, pages 370+ # Consider only the mono-species barley data (no competition from sinapis) d1 <- subset(dat, sseeds<1) d1 <- transform(d1, x=bseeds, y=bdwt, block=factor(block)) # Inverse yield looks like it will be a good fit for Gamma's inverse link libs(lattice) xyplot(1/y~x, data=d1, group=block, auto.key=list(columns=3), xlab="Seeding rate", ylab="Inverse yield of barley dry weight", main="streibig.competition") # linear predictor is quadratic, with separate intercept and slope per block m1 <- glm(y ~ block + block:x + x+I(x^2), data=d1, family=Gamma(link="inverse")) # Predict and plot newdf <- expand.grid(x=seq(0,120,length=50), block=factor(c('B1','B2','B3')) ) newdf\$pred <- predict(m1, new=newdf, type='response') plot(y~x, data=d1, col=block, main="streibig.competition - by block", xlab="Barley seeds", ylab="Barley dry weight") for(bb in 1:3){ newbb <- subset(newdf, block==c('B1','B2','B3')[bb]) lines(pred~x, data=newbb, col=bb) } ## End(Not run) ```

agridat documentation built on Dec. 20, 2021, 9:07 a.m.